Overview

Brought to you by YData

Dataset statistics

Number of variables39
Number of observations20358
Missing cells106723
Missing cells (%)13.4%
Duplicate rows579
Duplicate rows (%)2.8%
Total size in memory43.1 MiB
Average record size in memory2.2 KiB

Variable types

Numeric10
Categorical2
Text10
URL12
Unsupported1
Boolean2
DateTime2

Alerts

hireable has constant value "True" Constant
Dataset has 579 (2.8%) duplicate rowsDuplicates
actor_id is highly overall correlated with id and 2 other fieldsHigh correlation
followers is highly overall correlated with following and 6 other fieldsHigh correlation
following is highly overall correlated with followers and 4 other fieldsHigh correlation
id is highly overall correlated with actor_id and 2 other fieldsHigh correlation
log_followers is highly overall correlated with followers and 6 other fieldsHigh correlation
log_following is highly overall correlated with followers and 4 other fieldsHigh correlation
log_public_gists is highly overall correlated with actor_id and 6 other fieldsHigh correlation
log_public_repos is highly overall correlated with followers and 6 other fieldsHigh correlation
public_gists is highly overall correlated with actor_id and 6 other fieldsHigh correlation
public_repos is highly overall correlated with followers and 6 other fieldsHigh correlation
label is highly imbalanced (67.3%) Imbalance
type is highly imbalanced (92.9%) Imbalance
site_admin is highly imbalanced (95.8%) Imbalance
gravatar_id has 20358 (100.0%) missing values Missing
name has 2654 (13.0%) missing values Missing
company has 9229 (45.3%) missing values Missing
blog has 11601 (57.0%) missing values Missing
location has 7287 (35.8%) missing values Missing
email has 12079 (59.3%) missing values Missing
hireable has 16956 (83.3%) missing values Missing
bio has 11262 (55.3%) missing values Missing
twitter_username has 15297 (75.1%) missing values Missing
public_repos is highly skewed (γ1 = 54.5933405) Skewed
public_gists is highly skewed (γ1 = 75.17157706) Skewed
followers is highly skewed (γ1 = 32.59104167) Skewed
following is highly skewed (γ1 = 40.24260606) Skewed
gravatar_id is an unsupported type, check if it needs cleaning or further analysis Unsupported
public_repos has 964 (4.7%) zeros Zeros
public_gists has 8176 (40.2%) zeros Zeros
followers has 1476 (7.3%) zeros Zeros
following has 6189 (30.4%) zeros Zeros
log_public_repos has 964 (4.7%) zeros Zeros
log_public_gists has 8176 (40.2%) zeros Zeros
log_followers has 1476 (7.3%) zeros Zeros
log_following has 6189 (30.4%) zeros Zeros

Reproduction

Analysis started2024-11-22 14:03:41.664940
Analysis finished2024-11-22 14:04:09.530674
Duration27.87 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

actor_id
Real number (ℝ)

High correlation 

Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18757086
Minimum69
Maximum96406270
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.2 KiB
2024-11-22T22:04:09.966885image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum69
5-th percentile113268.75
Q11593194
median7942180.5
Q329485533
95-th percentile69631376
Maximum96406270
Range96406201
Interquartile range (IQR)27892339

Descriptive statistics

Standard deviation22858420
Coefficient of variation (CV)1.2186552
Kurtosis0.80517643
Mean18757086
Median Absolute Deviation (MAD)7442694
Skewness1.3549138
Sum3.8185675 × 1011
Variance5.2250735 × 1014
MonotonicityNot monotonic
2024-11-22T22:04:10.165960image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18622487 2
 
< 0.1%
37061471 2
 
< 0.1%
579279 2
 
< 0.1%
24435886 2
 
< 0.1%
11667869 2
 
< 0.1%
277935 2
 
< 0.1%
17150045 2
 
< 0.1%
6065744 2
 
< 0.1%
50326704 2
 
< 0.1%
12870617 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
69 1
< 0.1%
80 1
< 0.1%
139 1
< 0.1%
141 1
< 0.1%
159 1
< 0.1%
188 1
< 0.1%
211 1
< 0.1%
233 1
< 0.1%
235 1
< 0.1%
240 1
< 0.1%
ValueCountFrequency (%)
96406270 1
< 0.1%
95870427 1
< 0.1%
95593389 1
< 0.1%
95284144 1
< 0.1%
94929125 2
< 0.1%
94928193 1
< 0.1%
94923726 1
< 0.1%
94846361 1
< 0.1%
94798230 1
< 0.1%
94591206 1
< 0.1%

label
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
Human
19140 
Bot
 
1218

Length

Max length5
Median length5
Mean length4.8803419
Min length3

Characters and Unicode

Total characters99354
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowHuman
2nd rowHuman
3rd rowHuman
4th rowBot
5th rowHuman

Common Values

ValueCountFrequency (%)
Human 19140
94.0%
Bot 1218
 
6.0%

Length

2024-11-22T22:04:10.340719image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-22T22:04:10.517354image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
human 19140
94.0%
bot 1218
 
6.0%

Most occurring characters

ValueCountFrequency (%)
H 19140
19.3%
u 19140
19.3%
m 19140
19.3%
a 19140
19.3%
n 19140
19.3%
B 1218
 
1.2%
o 1218
 
1.2%
t 1218
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 78996
79.5%
Uppercase Letter 20358
 
20.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 19140
24.2%
m 19140
24.2%
a 19140
24.2%
n 19140
24.2%
o 1218
 
1.5%
t 1218
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
H 19140
94.0%
B 1218
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 99354
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
H 19140
19.3%
u 19140
19.3%
m 19140
19.3%
a 19140
19.3%
n 19140
19.3%
B 1218
 
1.2%
o 1218
 
1.2%
t 1218
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99354
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
H 19140
19.3%
u 19140
19.3%
m 19140
19.3%
a 19140
19.3%
n 19140
19.3%
B 1218
 
1.2%
o 1218
 
1.2%
t 1218
 
1.2%

login
Text

Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.3 MiB
2024-11-22T22:04:10.822787image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length35
Median length30
Mean length9.3264073
Min length1

Characters and Unicode

Total characters189867
Distinct characters65
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19178 ?
Unique (%)94.2%

Sample

1st rowdlazesz
2nd rowsarkiroka
3rd rowZoomQuiet
4th rowAlCutter
5th rowmeetyan
ValueCountFrequency (%)
g3rrus 2
 
< 0.1%
fractalwrench 2
 
< 0.1%
gruselhaus 2
 
< 0.1%
quodlibetor 2
 
< 0.1%
m1yag1 2
 
< 0.1%
agusioma 2
 
< 0.1%
ssreerama 2
 
< 0.1%
alexanderzobnin 2
 
< 0.1%
l1t1 2
 
< 0.1%
xuwei-k 2
 
< 0.1%
Other values (19758) 20338
99.9%
2024-11-22T22:04:11.355742image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 18606
 
9.8%
e 15853
 
8.3%
i 12452
 
6.6%
n 12246
 
6.4%
r 12001
 
6.3%
o 11776
 
6.2%
s 9467
 
5.0%
t 8605
 
4.5%
l 8492
 
4.5%
h 6634
 
3.5%
Other values (55) 73735
38.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 171560
90.4%
Uppercase Letter 8534
 
4.5%
Decimal Number 6605
 
3.5%
Dash Punctuation 2822
 
1.5%
Open Punctuation 173
 
0.1%
Close Punctuation 173
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 18606
 
10.8%
e 15853
 
9.2%
i 12452
 
7.3%
n 12246
 
7.1%
r 12001
 
7.0%
o 11776
 
6.9%
s 9467
 
5.5%
t 8605
 
5.0%
l 8492
 
4.9%
h 6634
 
3.9%
Other values (16) 55428
32.3%
Uppercase Letter
ValueCountFrequency (%)
S 838
 
9.8%
M 704
 
8.2%
A 602
 
7.1%
T 507
 
5.9%
C 482
 
5.6%
D 454
 
5.3%
B 431
 
5.1%
R 416
 
4.9%
J 411
 
4.8%
L 395
 
4.6%
Other values (16) 3294
38.6%
Decimal Number
ValueCountFrequency (%)
1 1232
18.7%
0 1112
16.8%
2 887
13.4%
3 634
9.6%
9 628
9.5%
7 463
 
7.0%
8 458
 
6.9%
4 453
 
6.9%
5 378
 
5.7%
6 360
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 2822
100.0%
Open Punctuation
ValueCountFrequency (%)
[ 173
100.0%
Close Punctuation
ValueCountFrequency (%)
] 173
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 180094
94.9%
Common 9773
 
5.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 18606
 
10.3%
e 15853
 
8.8%
i 12452
 
6.9%
n 12246
 
6.8%
r 12001
 
6.7%
o 11776
 
6.5%
s 9467
 
5.3%
t 8605
 
4.8%
l 8492
 
4.7%
h 6634
 
3.7%
Other values (42) 63962
35.5%
Common
ValueCountFrequency (%)
- 2822
28.9%
1 1232
12.6%
0 1112
 
11.4%
2 887
 
9.1%
3 634
 
6.5%
9 628
 
6.4%
7 463
 
4.7%
8 458
 
4.7%
4 453
 
4.6%
5 378
 
3.9%
Other values (3) 706
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 189867
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 18606
 
9.8%
e 15853
 
8.3%
i 12452
 
6.6%
n 12246
 
6.4%
r 12001
 
6.3%
o 11776
 
6.2%
s 9467
 
5.0%
t 8605
 
4.5%
l 8492
 
4.5%
h 6634
 
3.5%
Other values (55) 73735
38.8%

id
Real number (ℝ)

High correlation 

Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18757086
Minimum69
Maximum96406270
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size159.2 KiB
2024-11-22T22:04:11.580597image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum69
5-th percentile113268.75
Q11593194
median7942180.5
Q329485533
95-th percentile69631376
Maximum96406270
Range96406201
Interquartile range (IQR)27892339

Descriptive statistics

Standard deviation22858420
Coefficient of variation (CV)1.2186552
Kurtosis0.80517643
Mean18757086
Median Absolute Deviation (MAD)7442694
Skewness1.3549138
Sum3.8185675 × 1011
Variance5.2250735 × 1014
MonotonicityNot monotonic
2024-11-22T22:04:11.778960image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18622487 2
 
< 0.1%
37061471 2
 
< 0.1%
579279 2
 
< 0.1%
24435886 2
 
< 0.1%
11667869 2
 
< 0.1%
277935 2
 
< 0.1%
17150045 2
 
< 0.1%
6065744 2
 
< 0.1%
50326704 2
 
< 0.1%
12870617 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
69 1
< 0.1%
80 1
< 0.1%
139 1
< 0.1%
141 1
< 0.1%
159 1
< 0.1%
188 1
< 0.1%
211 1
< 0.1%
233 1
< 0.1%
235 1
< 0.1%
240 1
< 0.1%
ValueCountFrequency (%)
96406270 1
< 0.1%
95870427 1
< 0.1%
95593389 1
< 0.1%
95284144 1
< 0.1%
94929125 2
< 0.1%
94928193 1
< 0.1%
94923726 1
< 0.1%
94846361 1
< 0.1%
94798230 1
< 0.1%
94591206 1
< 0.1%
Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
2024-11-22T22:04:12.035831image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.793693
Min length12

Characters and Unicode

Total characters402960
Distinct characters64
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19178 ?
Unique (%)94.2%

Sample

1st rowMDQ6VXNlcjEwODE0MDU=
2nd rowMDQ6VXNlcjEzMTAwNTk4
3rd rowMDQ6VXNlcjIyNDk0
4th rowMDQ6VXNlcjc2NDgwMzI=
5th rowMDQ6VXNlcjIxNjM1MjI=
ValueCountFrequency (%)
mdq6vxnlcje4njiyndg3 2
 
< 0.1%
mdq6vxnlcjexodawnjqw 2
 
< 0.1%
mdq6vxnlcjmzmzgwmta3 2
 
< 0.1%
mdq6vxnlcji3nze2mq 2
 
< 0.1%
mdq6vxnlcjg3mza0mza 2
 
< 0.1%
mdq6vxnlcjq5mde5odi1 2
 
< 0.1%
mdq6vxnlcjc0ntcxodi5 2
 
< 0.1%
mdq6vxnlcjq5mzi4nte 2
 
< 0.1%
mdq6vxnlcjizmzaxnza0 2
 
< 0.1%
mdq6vxnlcjm4otc4nw 2
 
< 0.1%
Other values (19758) 20338
99.9%
2024-11-22T22:04:12.465650image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
M 42807
 
10.6%
N 35997
 
8.9%
D 31349
 
7.8%
j 27490
 
6.8%
Q 26949
 
6.7%
c 25144
 
6.2%
6 20296
 
5.0%
X 20146
 
5.0%
V 20128
 
5.0%
l 20126
 
5.0%
Other values (54) 132528
32.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 227975
56.6%
Lowercase Letter 111704
27.7%
Decimal Number 49696
 
12.3%
Math Symbol 13518
 
3.4%
Connector Punctuation 66
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M 42807
18.8%
N 35997
15.8%
D 31349
13.8%
Q 26949
11.8%
X 20146
8.8%
V 20128
8.8%
T 11039
 
4.8%
E 9006
 
4.0%
O 7888
 
3.5%
I 6660
 
2.9%
Other values (16) 16006
 
7.0%
Lowercase Letter
ValueCountFrequency (%)
j 27490
24.6%
c 25144
22.5%
l 20126
18.0%
z 12443
11.1%
w 5964
 
5.3%
g 5622
 
5.0%
y 5111
 
4.6%
x 4991
 
4.5%
k 4576
 
4.1%
m 174
 
0.2%
Other values (15) 63
 
0.1%
Decimal Number
ValueCountFrequency (%)
6 20296
40.8%
0 5139
 
10.3%
2 4918
 
9.9%
3 4836
 
9.7%
1 4832
 
9.7%
4 4768
 
9.6%
5 4724
 
9.5%
9 174
 
0.4%
8 6
 
< 0.1%
7 3
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
= 13518
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 339679
84.3%
Common 63281
 
15.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
M 42807
12.6%
N 35997
10.6%
D 31349
9.2%
j 27490
 
8.1%
Q 26949
 
7.9%
c 25144
 
7.4%
X 20146
 
5.9%
V 20128
 
5.9%
l 20126
 
5.9%
z 12443
 
3.7%
Other values (41) 77100
22.7%
Common
ValueCountFrequency (%)
6 20296
32.1%
= 13518
21.4%
0 5139
 
8.1%
2 4918
 
7.8%
3 4836
 
7.6%
1 4832
 
7.6%
4 4768
 
7.5%
5 4724
 
7.5%
9 174
 
0.3%
_ 66
 
0.1%
Other values (3) 10
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 402960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M 42807
 
10.6%
N 35997
 
8.9%
D 31349
 
7.8%
j 27490
 
6.8%
Q 26949
 
6.7%
c 25144
 
6.2%
6 20296
 
5.0%
X 20146
 
5.0%
V 20128
 
5.0%
l 20126
 
5.0%
Other values (54) 132528
32.9%
Distinct19761
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.1 MiB
https://avatars.githubusercontent.com/u/41768318?v=4
 
4
https://avatars.githubusercontent.com/u/18622487?v=4
 
2
https://avatars.githubusercontent.com/u/6065744?v=4
 
2
https://avatars.githubusercontent.com/u/3245568?v=4
 
2
https://avatars.githubusercontent.com/u/579279?v=4
 
2
Other values (19756)
20346 
ValueCountFrequency (%)
https://avatars.githubusercontent.com/u/41768318?v=4 4
 
< 0.1%
https://avatars.githubusercontent.com/u/18622487?v=4 2
 
< 0.1%
https://avatars.githubusercontent.com/u/6065744?v=4 2
 
< 0.1%
https://avatars.githubusercontent.com/u/3245568?v=4 2
 
< 0.1%
https://avatars.githubusercontent.com/u/579279?v=4 2
 
< 0.1%
https://avatars.githubusercontent.com/u/24435886?v=4 2
 
< 0.1%
https://avatars.githubusercontent.com/u/11667869?v=4 2
 
< 0.1%
https://avatars.githubusercontent.com/u/277935?v=4 2
 
< 0.1%
https://avatars.githubusercontent.com/u/17150045?v=4 2
 
< 0.1%
https://avatars.githubusercontent.com/u/37061471?v=4 2
 
< 0.1%
Other values (19751) 20336
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
avatars.githubusercontent.com 20358
100.0%
ValueCountFrequency (%)
/u/41768318 4
 
< 0.1%
/u/18622487 2
 
< 0.1%
/u/6065744 2
 
< 0.1%
/u/3245568 2
 
< 0.1%
/u/579279 2
 
< 0.1%
/u/24435886 2
 
< 0.1%
/u/11667869 2
 
< 0.1%
/u/277935 2
 
< 0.1%
/u/17150045 2
 
< 0.1%
/u/37061471 2
 
< 0.1%
Other values (19751) 20336
99.9%
ValueCountFrequency (%)
v=4 20358
100.0%
ValueCountFrequency (%)
20358
100.0%

gravatar_id
Unsupported

Missing  Rejected  Unsupported 

Missing20358
Missing (%)100.0%
Memory size159.2 KiB

url
URL

Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
https://api.github.com/users/G3rrus
 
2
https://api.github.com/users/ashwin1111
 
2
https://api.github.com/users/jfrolich
 
2
https://api.github.com/users/tsocha
 
2
https://api.github.com/users/thesamesam
 
2
Other values (19763)
20348 
ValueCountFrequency (%)
https://api.github.com/users/G3rrus 2
 
< 0.1%
https://api.github.com/users/ashwin1111 2
 
< 0.1%
https://api.github.com/users/jfrolich 2
 
< 0.1%
https://api.github.com/users/tsocha 2
 
< 0.1%
https://api.github.com/users/thesamesam 2
 
< 0.1%
https://api.github.com/users/plusgut 2
 
< 0.1%
https://api.github.com/users/vincenzopalazzo 2
 
< 0.1%
https://api.github.com/users/alexandrebodin 2
 
< 0.1%
https://api.github.com/users/teizenman 2
 
< 0.1%
https://api.github.com/users/yopito 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
api.github.com 20358
100.0%
ValueCountFrequency (%)
/users/G3rrus 2
 
< 0.1%
/users/ashwin1111 2
 
< 0.1%
/users/jfrolich 2
 
< 0.1%
/users/tsocha 2
 
< 0.1%
/users/thesamesam 2
 
< 0.1%
/users/plusgut 2
 
< 0.1%
/users/vincenzopalazzo 2
 
< 0.1%
/users/alexandrebodin 2
 
< 0.1%
/users/teizenman 2
 
< 0.1%
/users/yopito 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
20358
100.0%
ValueCountFrequency (%)
20358
100.0%
Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.7 MiB
https://github.com/G3rrus
 
2
https://github.com/ashwin1111
 
2
https://github.com/jfrolich
 
2
https://github.com/tsocha
 
2
https://github.com/thesamesam
 
2
Other values (19763)
20348 
ValueCountFrequency (%)
https://github.com/G3rrus 2
 
< 0.1%
https://github.com/ashwin1111 2
 
< 0.1%
https://github.com/jfrolich 2
 
< 0.1%
https://github.com/tsocha 2
 
< 0.1%
https://github.com/thesamesam 2
 
< 0.1%
https://github.com/plusgut 2
 
< 0.1%
https://github.com/vincenzopalazzo 2
 
< 0.1%
https://github.com/alexandrebodin 2
 
< 0.1%
https://github.com/teizenman 2
 
< 0.1%
https://github.com/yopito 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
github.com 20358
100.0%
ValueCountFrequency (%)
/G3rrus 2
 
< 0.1%
/ashwin1111 2
 
< 0.1%
/jfrolich 2
 
< 0.1%
/tsocha 2
 
< 0.1%
/thesamesam 2
 
< 0.1%
/plusgut 2
 
< 0.1%
/vincenzopalazzo 2
 
< 0.1%
/alexandrebodin 2
 
< 0.1%
/teizenman 2
 
< 0.1%
/yopito 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
20358
100.0%
ValueCountFrequency (%)
20358
100.0%
Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.0 MiB
https://api.github.com/users/G3rrus/followers
 
2
https://api.github.com/users/ashwin1111/followers
 
2
https://api.github.com/users/jfrolich/followers
 
2
https://api.github.com/users/tsocha/followers
 
2
https://api.github.com/users/thesamesam/followers
 
2
Other values (19763)
20348 
ValueCountFrequency (%)
https://api.github.com/users/G3rrus/followers 2
 
< 0.1%
https://api.github.com/users/ashwin1111/followers 2
 
< 0.1%
https://api.github.com/users/jfrolich/followers 2
 
< 0.1%
https://api.github.com/users/tsocha/followers 2
 
< 0.1%
https://api.github.com/users/thesamesam/followers 2
 
< 0.1%
https://api.github.com/users/plusgut/followers 2
 
< 0.1%
https://api.github.com/users/vincenzopalazzo/followers 2
 
< 0.1%
https://api.github.com/users/alexandrebodin/followers 2
 
< 0.1%
https://api.github.com/users/teizenman/followers 2
 
< 0.1%
https://api.github.com/users/yopito/followers 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
api.github.com 20358
100.0%
ValueCountFrequency (%)
/users/G3rrus/followers 2
 
< 0.1%
/users/ashwin1111/followers 2
 
< 0.1%
/users/jfrolich/followers 2
 
< 0.1%
/users/tsocha/followers 2
 
< 0.1%
/users/thesamesam/followers 2
 
< 0.1%
/users/plusgut/followers 2
 
< 0.1%
/users/vincenzopalazzo/followers 2
 
< 0.1%
/users/alexandrebodin/followers 2
 
< 0.1%
/users/teizenman/followers 2
 
< 0.1%
/users/yopito/followers 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
20358
100.0%
ValueCountFrequency (%)
20358
100.0%
Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
https://api.github.com/users/G3rrus/following{/other_user}
 
2
https://api.github.com/users/ashwin1111/following{/other_user}
 
2
https://api.github.com/users/jfrolich/following{/other_user}
 
2
https://api.github.com/users/tsocha/following{/other_user}
 
2
https://api.github.com/users/thesamesam/following{/other_user}
 
2
Other values (19763)
20348 
ValueCountFrequency (%)
https://api.github.com/users/G3rrus/following{/other_user} 2
 
< 0.1%
https://api.github.com/users/ashwin1111/following{/other_user} 2
 
< 0.1%
https://api.github.com/users/jfrolich/following{/other_user} 2
 
< 0.1%
https://api.github.com/users/tsocha/following{/other_user} 2
 
< 0.1%
https://api.github.com/users/thesamesam/following{/other_user} 2
 
< 0.1%
https://api.github.com/users/plusgut/following{/other_user} 2
 
< 0.1%
https://api.github.com/users/vincenzopalazzo/following{/other_user} 2
 
< 0.1%
https://api.github.com/users/alexandrebodin/following{/other_user} 2
 
< 0.1%
https://api.github.com/users/teizenman/following{/other_user} 2
 
< 0.1%
https://api.github.com/users/yopito/following{/other_user} 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
api.github.com 20358
100.0%
ValueCountFrequency (%)
/users/G3rrus/following{/other_user} 2
 
< 0.1%
/users/ashwin1111/following{/other_user} 2
 
< 0.1%
/users/jfrolich/following{/other_user} 2
 
< 0.1%
/users/tsocha/following{/other_user} 2
 
< 0.1%
/users/thesamesam/following{/other_user} 2
 
< 0.1%
/users/plusgut/following{/other_user} 2
 
< 0.1%
/users/vincenzopalazzo/following{/other_user} 2
 
< 0.1%
/users/alexandrebodin/following{/other_user} 2
 
< 0.1%
/users/teizenman/following{/other_user} 2
 
< 0.1%
/users/yopito/following{/other_user} 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
20358
100.0%
ValueCountFrequency (%)
20358
100.0%
Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
https://api.github.com/users/G3rrus/gists{/gist_id}
 
2
https://api.github.com/users/ashwin1111/gists{/gist_id}
 
2
https://api.github.com/users/jfrolich/gists{/gist_id}
 
2
https://api.github.com/users/tsocha/gists{/gist_id}
 
2
https://api.github.com/users/thesamesam/gists{/gist_id}
 
2
Other values (19763)
20348 
ValueCountFrequency (%)
https://api.github.com/users/G3rrus/gists{/gist_id} 2
 
< 0.1%
https://api.github.com/users/ashwin1111/gists{/gist_id} 2
 
< 0.1%
https://api.github.com/users/jfrolich/gists{/gist_id} 2
 
< 0.1%
https://api.github.com/users/tsocha/gists{/gist_id} 2
 
< 0.1%
https://api.github.com/users/thesamesam/gists{/gist_id} 2
 
< 0.1%
https://api.github.com/users/plusgut/gists{/gist_id} 2
 
< 0.1%
https://api.github.com/users/vincenzopalazzo/gists{/gist_id} 2
 
< 0.1%
https://api.github.com/users/alexandrebodin/gists{/gist_id} 2
 
< 0.1%
https://api.github.com/users/teizenman/gists{/gist_id} 2
 
< 0.1%
https://api.github.com/users/yopito/gists{/gist_id} 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
api.github.com 20358
100.0%
ValueCountFrequency (%)
/users/G3rrus/gists{/gist_id} 2
 
< 0.1%
/users/ashwin1111/gists{/gist_id} 2
 
< 0.1%
/users/jfrolich/gists{/gist_id} 2
 
< 0.1%
/users/tsocha/gists{/gist_id} 2
 
< 0.1%
/users/thesamesam/gists{/gist_id} 2
 
< 0.1%
/users/plusgut/gists{/gist_id} 2
 
< 0.1%
/users/vincenzopalazzo/gists{/gist_id} 2
 
< 0.1%
/users/alexandrebodin/gists{/gist_id} 2
 
< 0.1%
/users/teizenman/gists{/gist_id} 2
 
< 0.1%
/users/yopito/gists{/gist_id} 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
20358
100.0%
ValueCountFrequency (%)
20358
100.0%
Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.3 MiB
https://api.github.com/users/G3rrus/starred{/owner}{/repo}
 
2
https://api.github.com/users/ashwin1111/starred{/owner}{/repo}
 
2
https://api.github.com/users/jfrolich/starred{/owner}{/repo}
 
2
https://api.github.com/users/tsocha/starred{/owner}{/repo}
 
2
https://api.github.com/users/thesamesam/starred{/owner}{/repo}
 
2
Other values (19763)
20348 
ValueCountFrequency (%)
https://api.github.com/users/G3rrus/starred{/owner}{/repo} 2
 
< 0.1%
https://api.github.com/users/ashwin1111/starred{/owner}{/repo} 2
 
< 0.1%
https://api.github.com/users/jfrolich/starred{/owner}{/repo} 2
 
< 0.1%
https://api.github.com/users/tsocha/starred{/owner}{/repo} 2
 
< 0.1%
https://api.github.com/users/thesamesam/starred{/owner}{/repo} 2
 
< 0.1%
https://api.github.com/users/plusgut/starred{/owner}{/repo} 2
 
< 0.1%
https://api.github.com/users/vincenzopalazzo/starred{/owner}{/repo} 2
 
< 0.1%
https://api.github.com/users/alexandrebodin/starred{/owner}{/repo} 2
 
< 0.1%
https://api.github.com/users/teizenman/starred{/owner}{/repo} 2
 
< 0.1%
https://api.github.com/users/yopito/starred{/owner}{/repo} 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
api.github.com 20358
100.0%
ValueCountFrequency (%)
/users/G3rrus/starred{/owner}{/repo} 2
 
< 0.1%
/users/ashwin1111/starred{/owner}{/repo} 2
 
< 0.1%
/users/jfrolich/starred{/owner}{/repo} 2
 
< 0.1%
/users/tsocha/starred{/owner}{/repo} 2
 
< 0.1%
/users/thesamesam/starred{/owner}{/repo} 2
 
< 0.1%
/users/plusgut/starred{/owner}{/repo} 2
 
< 0.1%
/users/vincenzopalazzo/starred{/owner}{/repo} 2
 
< 0.1%
/users/alexandrebodin/starred{/owner}{/repo} 2
 
< 0.1%
/users/teizenman/starred{/owner}{/repo} 2
 
< 0.1%
/users/yopito/starred{/owner}{/repo} 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
20358
100.0%
ValueCountFrequency (%)
20358
100.0%
Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.1 MiB
https://api.github.com/users/G3rrus/subscriptions
 
2
https://api.github.com/users/ashwin1111/subscriptions
 
2
https://api.github.com/users/jfrolich/subscriptions
 
2
https://api.github.com/users/tsocha/subscriptions
 
2
https://api.github.com/users/thesamesam/subscriptions
 
2
Other values (19763)
20348 
ValueCountFrequency (%)
https://api.github.com/users/G3rrus/subscriptions 2
 
< 0.1%
https://api.github.com/users/ashwin1111/subscriptions 2
 
< 0.1%
https://api.github.com/users/jfrolich/subscriptions 2
 
< 0.1%
https://api.github.com/users/tsocha/subscriptions 2
 
< 0.1%
https://api.github.com/users/thesamesam/subscriptions 2
 
< 0.1%
https://api.github.com/users/plusgut/subscriptions 2
 
< 0.1%
https://api.github.com/users/vincenzopalazzo/subscriptions 2
 
< 0.1%
https://api.github.com/users/alexandrebodin/subscriptions 2
 
< 0.1%
https://api.github.com/users/teizenman/subscriptions 2
 
< 0.1%
https://api.github.com/users/yopito/subscriptions 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
api.github.com 20358
100.0%
ValueCountFrequency (%)
/users/G3rrus/subscriptions 2
 
< 0.1%
/users/ashwin1111/subscriptions 2
 
< 0.1%
/users/jfrolich/subscriptions 2
 
< 0.1%
/users/tsocha/subscriptions 2
 
< 0.1%
/users/thesamesam/subscriptions 2
 
< 0.1%
/users/plusgut/subscriptions 2
 
< 0.1%
/users/vincenzopalazzo/subscriptions 2
 
< 0.1%
/users/alexandrebodin/subscriptions 2
 
< 0.1%
/users/teizenman/subscriptions 2
 
< 0.1%
/users/yopito/subscriptions 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
20358
100.0%
ValueCountFrequency (%)
20358
100.0%
Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size1.9 MiB
https://api.github.com/users/G3rrus/orgs
 
2
https://api.github.com/users/ashwin1111/orgs
 
2
https://api.github.com/users/jfrolich/orgs
 
2
https://api.github.com/users/tsocha/orgs
 
2
https://api.github.com/users/thesamesam/orgs
 
2
Other values (19763)
20348 
ValueCountFrequency (%)
https://api.github.com/users/G3rrus/orgs 2
 
< 0.1%
https://api.github.com/users/ashwin1111/orgs 2
 
< 0.1%
https://api.github.com/users/jfrolich/orgs 2
 
< 0.1%
https://api.github.com/users/tsocha/orgs 2
 
< 0.1%
https://api.github.com/users/thesamesam/orgs 2
 
< 0.1%
https://api.github.com/users/plusgut/orgs 2
 
< 0.1%
https://api.github.com/users/vincenzopalazzo/orgs 2
 
< 0.1%
https://api.github.com/users/alexandrebodin/orgs 2
 
< 0.1%
https://api.github.com/users/teizenman/orgs 2
 
< 0.1%
https://api.github.com/users/yopito/orgs 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
api.github.com 20358
100.0%
ValueCountFrequency (%)
/users/G3rrus/orgs 2
 
< 0.1%
/users/ashwin1111/orgs 2
 
< 0.1%
/users/jfrolich/orgs 2
 
< 0.1%
/users/tsocha/orgs 2
 
< 0.1%
/users/thesamesam/orgs 2
 
< 0.1%
/users/plusgut/orgs 2
 
< 0.1%
/users/vincenzopalazzo/orgs 2
 
< 0.1%
/users/alexandrebodin/orgs 2
 
< 0.1%
/users/teizenman/orgs 2
 
< 0.1%
/users/yopito/orgs 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
20358
100.0%
ValueCountFrequency (%)
20358
100.0%
Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.0 MiB
https://api.github.com/users/G3rrus/repos
 
2
https://api.github.com/users/ashwin1111/repos
 
2
https://api.github.com/users/jfrolich/repos
 
2
https://api.github.com/users/tsocha/repos
 
2
https://api.github.com/users/thesamesam/repos
 
2
Other values (19763)
20348 
ValueCountFrequency (%)
https://api.github.com/users/G3rrus/repos 2
 
< 0.1%
https://api.github.com/users/ashwin1111/repos 2
 
< 0.1%
https://api.github.com/users/jfrolich/repos 2
 
< 0.1%
https://api.github.com/users/tsocha/repos 2
 
< 0.1%
https://api.github.com/users/thesamesam/repos 2
 
< 0.1%
https://api.github.com/users/plusgut/repos 2
 
< 0.1%
https://api.github.com/users/vincenzopalazzo/repos 2
 
< 0.1%
https://api.github.com/users/alexandrebodin/repos 2
 
< 0.1%
https://api.github.com/users/teizenman/repos 2
 
< 0.1%
https://api.github.com/users/yopito/repos 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
api.github.com 20358
100.0%
ValueCountFrequency (%)
/users/G3rrus/repos 2
 
< 0.1%
/users/ashwin1111/repos 2
 
< 0.1%
/users/jfrolich/repos 2
 
< 0.1%
/users/tsocha/repos 2
 
< 0.1%
/users/thesamesam/repos 2
 
< 0.1%
/users/plusgut/repos 2
 
< 0.1%
/users/vincenzopalazzo/repos 2
 
< 0.1%
/users/alexandrebodin/repos 2
 
< 0.1%
/users/teizenman/repos 2
 
< 0.1%
/users/yopito/repos 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
20358
100.0%
ValueCountFrequency (%)
20358
100.0%
Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
https://api.github.com/users/G3rrus/events{/privacy}
 
2
https://api.github.com/users/ashwin1111/events{/privacy}
 
2
https://api.github.com/users/jfrolich/events{/privacy}
 
2
https://api.github.com/users/tsocha/events{/privacy}
 
2
https://api.github.com/users/thesamesam/events{/privacy}
 
2
Other values (19763)
20348 
ValueCountFrequency (%)
https://api.github.com/users/G3rrus/events{/privacy} 2
 
< 0.1%
https://api.github.com/users/ashwin1111/events{/privacy} 2
 
< 0.1%
https://api.github.com/users/jfrolich/events{/privacy} 2
 
< 0.1%
https://api.github.com/users/tsocha/events{/privacy} 2
 
< 0.1%
https://api.github.com/users/thesamesam/events{/privacy} 2
 
< 0.1%
https://api.github.com/users/plusgut/events{/privacy} 2
 
< 0.1%
https://api.github.com/users/vincenzopalazzo/events{/privacy} 2
 
< 0.1%
https://api.github.com/users/alexandrebodin/events{/privacy} 2
 
< 0.1%
https://api.github.com/users/teizenman/events{/privacy} 2
 
< 0.1%
https://api.github.com/users/yopito/events{/privacy} 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
api.github.com 20358
100.0%
ValueCountFrequency (%)
/users/G3rrus/events{/privacy} 2
 
< 0.1%
/users/ashwin1111/events{/privacy} 2
 
< 0.1%
/users/jfrolich/events{/privacy} 2
 
< 0.1%
/users/tsocha/events{/privacy} 2
 
< 0.1%
/users/thesamesam/events{/privacy} 2
 
< 0.1%
/users/plusgut/events{/privacy} 2
 
< 0.1%
/users/vincenzopalazzo/events{/privacy} 2
 
< 0.1%
/users/alexandrebodin/events{/privacy} 2
 
< 0.1%
/users/teizenman/events{/privacy} 2
 
< 0.1%
/users/yopito/events{/privacy} 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
20358
100.0%
ValueCountFrequency (%)
20358
100.0%
Distinct19768
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
https://api.github.com/users/G3rrus/received_events
 
2
https://api.github.com/users/ashwin1111/received_events
 
2
https://api.github.com/users/jfrolich/received_events
 
2
https://api.github.com/users/tsocha/received_events
 
2
https://api.github.com/users/thesamesam/received_events
 
2
Other values (19763)
20348 
ValueCountFrequency (%)
https://api.github.com/users/G3rrus/received_events 2
 
< 0.1%
https://api.github.com/users/ashwin1111/received_events 2
 
< 0.1%
https://api.github.com/users/jfrolich/received_events 2
 
< 0.1%
https://api.github.com/users/tsocha/received_events 2
 
< 0.1%
https://api.github.com/users/thesamesam/received_events 2
 
< 0.1%
https://api.github.com/users/plusgut/received_events 2
 
< 0.1%
https://api.github.com/users/vincenzopalazzo/received_events 2
 
< 0.1%
https://api.github.com/users/alexandrebodin/received_events 2
 
< 0.1%
https://api.github.com/users/teizenman/received_events 2
 
< 0.1%
https://api.github.com/users/yopito/received_events 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
https 20358
100.0%
ValueCountFrequency (%)
api.github.com 20358
100.0%
ValueCountFrequency (%)
/users/G3rrus/received_events 2
 
< 0.1%
/users/ashwin1111/received_events 2
 
< 0.1%
/users/jfrolich/received_events 2
 
< 0.1%
/users/tsocha/received_events 2
 
< 0.1%
/users/thesamesam/received_events 2
 
< 0.1%
/users/plusgut/received_events 2
 
< 0.1%
/users/vincenzopalazzo/received_events 2
 
< 0.1%
/users/alexandrebodin/received_events 2
 
< 0.1%
/users/teizenman/received_events 2
 
< 0.1%
/users/yopito/received_events 2
 
< 0.1%
Other values (19758) 20338
99.9%
ValueCountFrequency (%)
20358
100.0%
ValueCountFrequency (%)
20358
100.0%

type
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
User
20185 
Bot
 
173

Length

Max length4
Median length4
Mean length3.9915021
Min length3

Characters and Unicode

Total characters81259
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUser
2nd rowUser
3rd rowUser
4th rowUser
5th rowUser

Common Values

ValueCountFrequency (%)
User 20185
99.2%
Bot 173
 
0.8%

Length

2024-11-22T22:04:12.671660image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-22T22:04:12.802768image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
ValueCountFrequency (%)
user 20185
99.2%
bot 173
 
0.8%

Most occurring characters

ValueCountFrequency (%)
U 20185
24.8%
s 20185
24.8%
e 20185
24.8%
r 20185
24.8%
B 173
 
0.2%
o 173
 
0.2%
t 173
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 60901
74.9%
Uppercase Letter 20358
 
25.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 20185
33.1%
e 20185
33.1%
r 20185
33.1%
o 173
 
0.3%
t 173
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
U 20185
99.2%
B 173
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 81259
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
U 20185
24.8%
s 20185
24.8%
e 20185
24.8%
r 20185
24.8%
B 173
 
0.2%
o 173
 
0.2%
t 173
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81259
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
U 20185
24.8%
s 20185
24.8%
e 20185
24.8%
r 20185
24.8%
B 173
 
0.2%
o 173
 
0.2%
t 173
 
0.2%

site_admin
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.0 KiB
False
20265 
True
 
93
ValueCountFrequency (%)
False 20265
99.5%
True 93
 
0.5%
2024-11-22T22:04:12.935699image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

name
Text

Missing 

Distinct16972
Distinct (%)95.9%
Missing2654
Missing (%)13.0%
Memory size1.3 MiB
2024-11-22T22:04:13.331986image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length49
Median length38
Mean length12.626582
Min length1

Characters and Unicode

Total characters223541
Distinct characters625
Distinct categories19 ?
Distinct scripts15 ?
Distinct blocks26 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16304 ?
Unique (%)92.1%

Sample

1st rowIndig Balázs
2nd rowsarkiroka
3rd rowZoom.Quiet
4th rowAl Cutter
5th rowJiajun Yan
ValueCountFrequency (%)
david 199
 
0.6%
michael 176
 
0.5%
bot 162
 
0.5%
daniel 159
 
0.5%
chris 131
 
0.4%
thomas 123
 
0.4%
alex 117
 
0.3%
andrew 105
 
0.3%
john 100
 
0.3%
martin 96
 
0.3%
Other values (17716) 33228
96.0%
2024-11-22T22:04:13.978118image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 21517
 
9.6%
e 17622
 
7.9%
16949
 
7.6%
i 15280
 
6.8%
n 15264
 
6.8%
r 13048
 
5.8%
o 11996
 
5.4%
l 9042
 
4.0%
s 8057
 
3.6%
t 7727
 
3.5%
Other values (615) 87039
38.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 169014
75.6%
Uppercase Letter 35267
 
15.8%
Space Separator 16950
 
7.6%
Other Punctuation 651
 
0.3%
Decimal Number 408
 
0.2%
Other Letter 393
 
0.2%
Dash Punctuation 386
 
0.2%
Close Punctuation 175
 
0.1%
Open Punctuation 174
 
0.1%
Nonspacing Mark 36
 
< 0.1%
Other values (9) 87
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6
 
1.5%
4
 
1.0%
4
 
1.0%
4
 
1.0%
4
 
1.0%
4
 
1.0%
4
 
1.0%
4
 
1.0%
3
 
0.8%
3
 
0.8%
Other values (290) 353
89.8%
Lowercase Letter
ValueCountFrequency (%)
a 21517
12.7%
e 17622
10.4%
i 15280
 
9.0%
n 15264
 
9.0%
r 13048
 
7.7%
o 11996
 
7.1%
l 9042
 
5.3%
s 8057
 
4.8%
t 7727
 
4.6%
h 7090
 
4.2%
Other values (144) 42371
25.1%
Uppercase Letter
ValueCountFrequency (%)
S 3153
 
8.9%
M 3140
 
8.9%
A 2718
 
7.7%
J 2111
 
6.0%
B 2088
 
5.9%
C 1930
 
5.5%
D 1910
 
5.4%
K 1781
 
5.1%
R 1658
 
4.7%
P 1607
 
4.6%
Other values (60) 13171
37.3%
Nonspacing Mark
ValueCountFrequency (%)
̼ 3
 
8.3%
̩ 2
 
5.6%
̃ 2
 
5.6%
̝ 2
 
5.6%
2
 
5.6%
1
 
2.8%
̗ 1
 
2.8%
̞ 1
 
2.8%
̎ 1
 
2.8%
̏ 1
 
2.8%
Other values (20) 20
55.6%
Other Punctuation
ValueCountFrequency (%)
. 453
69.6%
' 58
 
8.9%
" 44
 
6.8%
, 38
 
5.8%
/ 24
 
3.7%
@ 14
 
2.2%
: 6
 
0.9%
! 4
 
0.6%
· 3
 
0.5%
& 1
 
0.2%
Other values (6) 6
 
0.9%
Other Symbol
ValueCountFrequency (%)
3
16.7%
3
16.7%
® 2
11.1%
2
11.1%
2
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Decimal Number
ValueCountFrequency (%)
1 87
21.3%
2 52
12.7%
0 49
12.0%
8 38
9.3%
3 36
8.8%
4 35
8.6%
5 31
 
7.6%
6 29
 
7.1%
9 26
 
6.4%
7 25
 
6.1%
Modifier Letter
ValueCountFrequency (%)
3
30.0%
ʲ 3
30.0%
ˈ 1
 
10.0%
ˌ 1
 
10.0%
1
 
10.0%
1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 152
86.9%
] 14
 
8.0%
} 5
 
2.9%
3
 
1.7%
1
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 151
86.8%
[ 14
 
8.0%
{ 5
 
2.9%
3
 
1.7%
1
 
0.6%
Spacing Mark
ValueCountFrequency (%)
1
20.0%
1
20.0%
ि 1
20.0%
ਿ 1
20.0%
1
20.0%
Math Symbol
ValueCountFrequency (%)
< 4
30.8%
> 4
30.8%
| 4
30.8%
~ 1
 
7.7%
Space Separator
ValueCountFrequency (%)
16949
> 99.9%
  1
 
< 0.1%
Connector Punctuation
ValueCountFrequency (%)
_ 30
96.8%
1
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 386
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 6
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Other Number
ValueCountFrequency (%)
1
100.0%
Format
ValueCountFrequency (%)
 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 204065
91.3%
Common 18820
 
8.4%
Han 279
 
0.1%
Cyrillic 196
 
0.1%
Hangul 44
 
< 0.1%
Inherited 34
 
< 0.1%
Hiragana 26
 
< 0.1%
Katakana 25
 
< 0.1%
Greek 24
 
< 0.1%
Gurmukhi 10
 
< 0.1%
Other values (5) 18
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
6
 
2.2%
4
 
1.4%
4
 
1.4%
4
 
1.4%
4
 
1.4%
4
 
1.4%
3
 
1.1%
3
 
1.1%
3
 
1.1%
3
 
1.1%
Other values (202) 241
86.4%
Latin
ValueCountFrequency (%)
a 21517
 
10.5%
e 17622
 
8.6%
i 15280
 
7.5%
n 15264
 
7.5%
r 13048
 
6.4%
o 11996
 
5.9%
l 9042
 
4.4%
s 8057
 
3.9%
t 7727
 
3.8%
h 7090
 
3.5%
Other values (156) 77422
37.9%
Common
ValueCountFrequency (%)
16949
90.1%
. 453
 
2.4%
- 386
 
2.1%
) 152
 
0.8%
( 151
 
0.8%
1 87
 
0.5%
' 58
 
0.3%
2 52
 
0.3%
0 49
 
0.3%
" 44
 
0.2%
Other values (52) 439
 
2.3%
Cyrillic
ValueCountFrequency (%)
а 21
 
10.7%
н 17
 
8.7%
е 16
 
8.2%
в 14
 
7.1%
о 14
 
7.1%
и 13
 
6.6%
р 11
 
5.6%
л 8
 
4.1%
с 6
 
3.1%
т 6
 
3.1%
Other values (33) 70
35.7%
Hangul
ValueCountFrequency (%)
4
 
9.1%
3
 
6.8%
3
 
6.8%
2
 
4.5%
2
 
4.5%
2
 
4.5%
2
 
4.5%
2
 
4.5%
1
 
2.3%
1
 
2.3%
Other values (22) 22
50.0%
Inherited
ValueCountFrequency (%)
̼ 3
 
8.8%
̩ 2
 
5.9%
̃ 2
 
5.9%
̝ 2
 
5.9%
2
 
5.9%
̗ 1
 
2.9%
̞ 1
 
2.9%
̎ 1
 
2.9%
̏ 1
 
2.9%
̅ 1
 
2.9%
Other values (18) 18
52.9%
Hiragana
ValueCountFrequency (%)
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (13) 13
50.0%
Greek
ValueCountFrequency (%)
ι 4
16.7%
Λ 3
12.5%
τ 2
 
8.3%
α 2
 
8.3%
Σ 1
 
4.2%
λ 1
 
4.2%
γ 1
 
4.2%
ο 1
 
4.2%
Φ 1
 
4.2%
Ξ 1
 
4.2%
Other values (7) 7
29.2%
Katakana
ValueCountFrequency (%)
4
16.0%
3
12.0%
2
 
8.0%
2
 
8.0%
2
 
8.0%
2
 
8.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
Other values (6) 6
24.0%
Gurmukhi
ValueCountFrequency (%)
2
20.0%
1
10.0%
1
10.0%
ਿ 1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Devanagari
ValueCountFrequency (%)
2
25.0%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
ि 1
12.5%
Runic
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Arabic
ValueCountFrequency (%)
م 1
100.0%
Georgian
ValueCountFrequency (%)
1
100.0%
Sinhala
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 221576
99.1%
None 1265
 
0.6%
CJK 279
 
0.1%
Cyrillic 196
 
0.1%
Hangul 44
 
< 0.1%
Diacriticals 32
 
< 0.1%
Katakana 29
 
< 0.1%
Hiragana 26
 
< 0.1%
Latin Ext Additional 14
 
< 0.1%
IPA Ext 13
 
< 0.1%
Other values (16) 67
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 21517
 
9.7%
e 17622
 
8.0%
16949
 
7.6%
i 15280
 
6.9%
n 15264
 
6.9%
r 13048
 
5.9%
o 11996
 
5.4%
l 9042
 
4.1%
s 8057
 
3.6%
t 7727
 
3.5%
Other values (77) 85074
38.4%
None
ValueCountFrequency (%)
é 224
17.7%
á 132
 
10.4%
í 74
 
5.8%
ö 64
 
5.1%
ü 63
 
5.0%
ó 58
 
4.6%
ł 53
 
4.2%
š 33
 
2.6%
ä 33
 
2.6%
ø 28
 
2.2%
Other values (102) 503
39.8%
Cyrillic
ValueCountFrequency (%)
а 21
 
10.7%
н 17
 
8.7%
е 16
 
8.2%
в 14
 
7.1%
о 14
 
7.1%
и 13
 
6.6%
р 11
 
5.6%
л 8
 
4.1%
с 6
 
3.1%
т 6
 
3.1%
Other values (33) 70
35.7%
CJK
ValueCountFrequency (%)
6
 
2.2%
4
 
1.4%
4
 
1.4%
4
 
1.4%
4
 
1.4%
4
 
1.4%
3
 
1.1%
3
 
1.1%
3
 
1.1%
3
 
1.1%
Other values (202) 241
86.4%
Hangul
ValueCountFrequency (%)
4
 
9.1%
3
 
6.8%
3
 
6.8%
2
 
4.5%
2
 
4.5%
2
 
4.5%
2
 
4.5%
2
 
4.5%
1
 
2.3%
1
 
2.3%
Other values (22) 22
50.0%
Katakana
ValueCountFrequency (%)
4
13.8%
3
 
10.3%
3
 
10.3%
2
 
6.9%
2
 
6.9%
2
 
6.9%
2
 
6.9%
1
 
3.4%
1
 
3.4%
1
 
3.4%
Other values (8) 8
27.6%
Latin Ext Additional
ValueCountFrequency (%)
4
28.6%
3
21.4%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
ế 1
 
7.1%
Misc Symbols
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Modifier Letters
ValueCountFrequency (%)
ʲ 3
60.0%
ˈ 1
 
20.0%
ˌ 1
 
20.0%
Phonetic Ext
ValueCountFrequency (%)
3
25.0%
2
16.7%
2
16.7%
1
 
8.3%
1
 
8.3%
1
 
8.3%
1
 
8.3%
1
 
8.3%
IPA Ext
ValueCountFrequency (%)
ʀ 3
23.1%
ɡ 1
 
7.7%
ɪ 1
 
7.7%
ʈ 1
 
7.7%
ɢ 1
 
7.7%
ʜ 1
 
7.7%
ɴ 1
 
7.7%
ɵ 1
 
7.7%
ɨ 1
 
7.7%
ʍ 1
 
7.7%
Diacriticals
ValueCountFrequency (%)
̼ 3
 
9.4%
̩ 2
 
6.2%
̃ 2
 
6.2%
̝ 2
 
6.2%
̗ 1
 
3.1%
̞ 1
 
3.1%
̎ 1
 
3.1%
̏ 1
 
3.1%
̅ 1
 
3.1%
͝ 1
 
3.1%
Other values (17) 17
53.1%
Geometric Shapes
ValueCountFrequency (%)
3
75.0%
1
 
25.0%
Hiragana
ValueCountFrequency (%)
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (13) 13
50.0%
Gurmukhi
ValueCountFrequency (%)
2
20.0%
1
10.0%
1
10.0%
ਿ 1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
1
10.0%
Letterlike Symbols
ValueCountFrequency (%)
2
100.0%
VS
ValueCountFrequency (%)
2
100.0%
Dingbats
ValueCountFrequency (%)
2
66.7%
1
33.3%
Devanagari
ValueCountFrequency (%)
2
25.0%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
ि 1
12.5%
Punctuation
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Runic
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Arabic
ValueCountFrequency (%)
م 1
100.0%
Georgian
ValueCountFrequency (%)
1
100.0%
Misc Technical
ValueCountFrequency (%)
1
50.0%
1
50.0%
Arrows
ValueCountFrequency (%)
1
100.0%
Sinhala
ValueCountFrequency (%)
1
100.0%

company
Text

Missing 

Distinct6494
Distinct (%)58.4%
Missing9229
Missing (%)45.3%
Memory size1.0 MiB
2024-11-22T22:04:14.357198image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length211
Median length95
Mean length12.686135
Min length1

Characters and Unicode

Total characters141184
Distinct characters227
Distinct categories17 ?
Distinct scripts8 ?
Distinct blocks15 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5545 ?
Unique (%)49.8%

Sample

1st row蟒营® py.101.camp
2nd rowAlpega
3rd rowMOONGIFT
4th rowGoogle
5th row@Wikia
ValueCountFrequency (%)
microsoft 808
 
4.6%
red 544
 
3.1%
hat 543
 
3.1%
university 320
 
1.8%
google 312
 
1.8%
269
 
1.5%
of 265
 
1.5%
inc 258
 
1.5%
intel 172
 
1.0%
automattic 168
 
1.0%
Other values (6753) 13992
79.3%
2024-11-22T22:04:14.922794image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 10995
 
7.8%
o 10446
 
7.4%
a 9367
 
6.6%
t 8908
 
6.3%
i 8605
 
6.1%
8429
 
6.0%
r 7188
 
5.1%
n 6657
 
4.7%
s 6002
 
4.3%
@ 5766
 
4.1%
Other values (217) 58821
41.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 104918
74.3%
Uppercase Letter 18220
 
12.9%
Space Separator 8429
 
6.0%
Other Punctuation 7475
 
5.3%
Dash Punctuation 1162
 
0.8%
Decimal Number 492
 
0.3%
Open Punctuation 121
 
0.1%
Close Punctuation 120
 
0.1%
Other Letter 116
 
0.1%
Math Symbol 72
 
0.1%
Other values (7) 59
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
ʔ 5
 
4.3%
4
 
3.4%
4
 
3.4%
4
 
3.4%
4
 
3.4%
3
 
2.6%
3
 
2.6%
2
 
1.7%
2
 
1.7%
2
 
1.7%
Other values (76) 83
71.6%
Lowercase Letter
ValueCountFrequency (%)
e 10995
10.5%
o 10446
 
10.0%
a 9367
 
8.9%
t 8908
 
8.5%
i 8605
 
8.2%
r 7188
 
6.9%
n 6657
 
6.3%
s 6002
 
5.7%
c 5295
 
5.0%
l 4701
 
4.5%
Other values (36) 26754
25.5%
Uppercase Letter
ValueCountFrequency (%)
S 1677
 
9.2%
M 1492
 
8.2%
A 1376
 
7.6%
C 1340
 
7.4%
I 1308
 
7.2%
H 1088
 
6.0%
R 1043
 
5.7%
L 900
 
4.9%
T 827
 
4.5%
G 760
 
4.2%
Other values (18) 6409
35.2%
Other Punctuation
ValueCountFrequency (%)
@ 5766
77.1%
. 719
 
9.6%
, 534
 
7.1%
/ 256
 
3.4%
: 72
 
1.0%
& 67
 
0.9%
' 26
 
0.3%
6
 
0.1%
; 6
 
0.1%
" 6
 
0.1%
Other values (7) 17
 
0.2%
Other Symbol
ValueCountFrequency (%)
8
30.8%
® 5
19.2%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (4) 4
15.4%
Decimal Number
ValueCountFrequency (%)
2 122
24.8%
1 69
14.0%
0 65
13.2%
4 55
11.2%
3 51
10.4%
8 36
 
7.3%
6 26
 
5.3%
5 25
 
5.1%
7 24
 
4.9%
9 19
 
3.9%
Nonspacing Mark
ValueCountFrequency (%)
̅ 4
26.7%
͡ 4
26.7%
̫ 3
20.0%
͜ 2
13.3%
͓ 1
 
6.7%
1
 
6.7%
Math Symbol
ValueCountFrequency (%)
| 49
68.1%
+ 21
29.2%
= 1
 
1.4%
> 1
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 1157
99.6%
3
 
0.3%
2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 114
94.2%
[ 4
 
3.3%
{ 3
 
2.5%
Close Punctuation
ValueCountFrequency (%)
) 113
94.2%
] 4
 
3.3%
} 3
 
2.5%
Modifier Symbol
ValueCountFrequency (%)
` 4
66.7%
¯ 2
33.3%
Space Separator
ValueCountFrequency (%)
8429
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 9
100.0%
Format
ValueCountFrequency (%)
1
100.0%
Modifier Letter
ValueCountFrequency (%)
1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 123143
87.2%
Common 17899
 
12.7%
Han 75
 
0.1%
Hiragana 18
 
< 0.1%
Braille 16
 
< 0.1%
Inherited 15
 
< 0.1%
Katakana 15
 
< 0.1%
Hangul 3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 10995
 
8.9%
o 10446
 
8.5%
a 9367
 
7.6%
t 8908
 
7.2%
i 8605
 
7.0%
r 7188
 
5.8%
n 6657
 
5.4%
s 6002
 
4.9%
c 5295
 
4.3%
l 4701
 
3.8%
Other values (65) 44979
36.5%
Common
ValueCountFrequency (%)
8429
47.1%
@ 5766
32.2%
- 1157
 
6.5%
. 719
 
4.0%
, 534
 
3.0%
/ 256
 
1.4%
2 122
 
0.7%
( 114
 
0.6%
) 113
 
0.6%
: 72
 
0.4%
Other values (43) 617
 
3.4%
Han
ValueCountFrequency (%)
4
 
5.3%
4
 
5.3%
4
 
5.3%
4
 
5.3%
3
 
4.0%
3
 
4.0%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
Other values (41) 45
60.0%
Hiragana
ValueCountFrequency (%)
2
 
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (7) 7
38.9%
Katakana
ValueCountFrequency (%)
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (4) 4
26.7%
Braille
ValueCountFrequency (%)
8
50.0%
2
 
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Inherited
ValueCountFrequency (%)
̅ 4
26.7%
͡ 4
26.7%
̫ 3
20.0%
͜ 2
13.3%
͓ 1
 
6.7%
1
 
6.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 140910
99.8%
None 98
 
0.1%
CJK 75
 
0.1%
Hiragana 18
 
< 0.1%
Braille 16
 
< 0.1%
Katakana 16
 
< 0.1%
IPA Ext 15
 
< 0.1%
Diacriticals 14
 
< 0.1%
Punctuation 13
 
< 0.1%
Hangul 3
 
< 0.1%
Other values (5) 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 10995
 
7.8%
o 10446
 
7.4%
a 9367
 
6.6%
t 8908
 
6.3%
i 8605
 
6.1%
8429
 
6.0%
r 7188
 
5.1%
n 6657
 
4.7%
s 6002
 
4.3%
@ 5766
 
4.1%
Other values (79) 58547
41.5%
None
ValueCountFrequency (%)
é 24
24.5%
ä 11
11.2%
ó 10
10.2%
ü 9
 
9.2%
ð 5
 
5.1%
Ü 5
 
5.1%
® 5
 
5.1%
ú 3
 
3.1%
É 3
 
3.1%
í 3
 
3.1%
Other values (14) 20
20.4%
Braille
ValueCountFrequency (%)
8
50.0%
2
 
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Punctuation
ValueCountFrequency (%)
6
46.2%
3
23.1%
2
 
15.4%
1
 
7.7%
1
 
7.7%
IPA Ext
ValueCountFrequency (%)
ʔ 5
33.3%
ʘ 4
26.7%
ʕ 4
26.7%
ɛ 2
 
13.3%
CJK
ValueCountFrequency (%)
4
 
5.3%
4
 
5.3%
4
 
5.3%
4
 
5.3%
3
 
4.0%
3
 
4.0%
2
 
2.7%
2
 
2.7%
2
 
2.7%
2
 
2.7%
Other values (41) 45
60.0%
Diacriticals
ValueCountFrequency (%)
̅ 4
28.6%
͡ 4
28.6%
̫ 3
21.4%
͜ 2
14.3%
͓ 1
 
7.1%
Hiragana
ValueCountFrequency (%)
2
 
11.1%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
1
 
5.6%
Other values (7) 7
38.9%
Katakana
ValueCountFrequency (%)
2
 
12.5%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (5) 5
31.2%
Dingbats
ValueCountFrequency (%)
1
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
VS
ValueCountFrequency (%)
1
100.0%
Misc Symbols
ValueCountFrequency (%)
1
50.0%
1
50.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

blog
Text

Missing 

Distinct8448
Distinct (%)96.5%
Missing11601
Missing (%)57.0%
Memory size1.0 MiB
2024-11-22T22:04:15.175998image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length145
Median length86
Mean length24.285943
Min length1

Characters and Unicode

Total characters212672
Distinct characters128
Distinct categories12 ?
Distinct scripts6 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8158 ?
Unique (%)93.2%

Sample

1st rowhttps://sarkiroka.hu
2nd rowhttp://zoomquiet.io
3rd rowhttps://www.patreon.com/buddyspencer
4th rowhttps://moongift.co.jp
5th rowhttp://jamie.sh
ValueCountFrequency (%)
https://www.odoo.com 6
 
0.1%
www.taosdata.com 5
 
0.1%
https://review.docs.microsoft.com/en-us/engineering/projects/ops/engdocs/how-to-grant-service-account-permission-in-your-repository?branch=master 5
 
0.1%
http://github.com/openshift 4
 
< 0.1%
https://www.sap.com 4
 
< 0.1%
https://adguard.com 4
 
< 0.1%
https://mattermost.com 3
 
< 0.1%
https://www.dhis2.org 3
 
< 0.1%
https://www.microsoft.com 3
 
< 0.1%
https://codecov.io 3
 
< 0.1%
Other values (8431) 8728
99.5%
2024-11-22T22:04:15.626154image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 21382
 
10.1%
/ 19248
 
9.1%
. 12850
 
6.0%
o 12708
 
6.0%
h 11422
 
5.4%
s 11415
 
5.4%
e 11211
 
5.3%
i 10759
 
5.1%
p 9571
 
4.5%
a 9321
 
4.4%
Other values (118) 82785
38.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 168280
79.1%
Other Punctuation 39586
 
18.6%
Decimal Number 2725
 
1.3%
Dash Punctuation 1097
 
0.5%
Uppercase Letter 731
 
0.3%
Math Symbol 113
 
0.1%
Connector Punctuation 79
 
< 0.1%
Other Letter 22
 
< 0.1%
Space Separator 17
 
< 0.1%
Open Punctuation 9
 
< 0.1%
Other values (2) 13
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 21382
 
12.7%
o 12708
 
7.6%
h 11422
 
6.8%
s 11415
 
6.8%
e 11211
 
6.7%
i 10759
 
6.4%
p 9571
 
5.7%
a 9321
 
5.5%
n 8391
 
5.0%
c 7457
 
4.4%
Other values (35) 54643
32.5%
Uppercase Letter
ValueCountFrequency (%)
A 65
 
8.9%
S 52
 
7.1%
M 48
 
6.6%
C 42
 
5.7%
D 41
 
5.6%
I 36
 
4.9%
T 35
 
4.8%
P 34
 
4.7%
B 32
 
4.4%
G 30
 
4.1%
Other values (16) 316
43.2%
Other Letter
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (9) 9
40.9%
Other Punctuation
ValueCountFrequency (%)
/ 19248
48.6%
. 12850
32.5%
: 7210
 
18.2%
@ 192
 
0.5%
? 37
 
0.1%
% 17
 
< 0.1%
# 14
 
< 0.1%
! 6
 
< 0.1%
& 5
 
< 0.1%
; 2
 
< 0.1%
Other values (3) 5
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
1 462
17.0%
0 421
15.4%
2 302
11.1%
3 273
10.0%
7 235
8.6%
8 220
8.1%
5 214
7.9%
9 213
7.8%
4 211
7.7%
6 174
 
6.4%
Math Symbol
ValueCountFrequency (%)
~ 72
63.7%
= 39
34.5%
| 1
 
0.9%
< 1
 
0.9%
Open Punctuation
ValueCountFrequency (%)
{ 5
55.6%
( 2
 
22.2%
[ 2
 
22.2%
Close Punctuation
ValueCountFrequency (%)
} 5
55.6%
) 2
 
22.2%
] 2
 
22.2%
Dash Punctuation
ValueCountFrequency (%)
- 1096
99.9%
1
 
0.1%
Connector Punctuation
ValueCountFrequency (%)
_ 79
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 168987
79.5%
Common 43639
 
20.5%
Cyrillic 16
 
< 0.1%
Han 16
 
< 0.1%
Greek 8
 
< 0.1%
Hiragana 6
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 21382
 
12.7%
o 12708
 
7.5%
h 11422
 
6.8%
s 11415
 
6.8%
e 11211
 
6.6%
i 10759
 
6.4%
p 9571
 
5.7%
a 9321
 
5.5%
n 8391
 
5.0%
c 7457
 
4.4%
Other values (47) 55350
32.8%
Common
ValueCountFrequency (%)
/ 19248
44.1%
. 12850
29.4%
: 7210
 
16.5%
- 1096
 
2.5%
1 462
 
1.1%
0 421
 
1.0%
2 302
 
0.7%
3 273
 
0.6%
7 235
 
0.5%
8 220
 
0.5%
Other values (28) 1322
 
3.0%
Han
ValueCountFrequency (%)
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (6) 6
37.5%
Cyrillic
ValueCountFrequency (%)
н 3
18.8%
а 3
18.8%
о 2
12.5%
к 1
 
6.2%
е 1
 
6.2%
р 1
 
6.2%
т 1
 
6.2%
д 1
 
6.2%
с 1
 
6.2%
л 1
 
6.2%
Greek
ValueCountFrequency (%)
λ 3
37.5%
π 3
37.5%
ω 2
25.0%
Hiragana
ValueCountFrequency (%)
2
33.3%
2
33.3%
2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 212618
> 99.9%
Cyrillic 16
 
< 0.1%
CJK 16
 
< 0.1%
None 15
 
< 0.1%
Hiragana 6
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 21382
 
10.1%
/ 19248
 
9.1%
. 12850
 
6.0%
o 12708
 
6.0%
h 11422
 
5.4%
s 11415
 
5.4%
e 11211
 
5.3%
i 10759
 
5.1%
p 9571
 
4.5%
a 9321
 
4.4%
Other values (78) 82731
38.9%
Cyrillic
ValueCountFrequency (%)
н 3
18.8%
а 3
18.8%
о 2
12.5%
к 1
 
6.2%
е 1
 
6.2%
р 1
 
6.2%
т 1
 
6.2%
д 1
 
6.2%
с 1
 
6.2%
л 1
 
6.2%
None
ValueCountFrequency (%)
λ 3
20.0%
π 3
20.0%
ω 2
13.3%
ö 2
13.3%
ä 1
 
6.7%
ß 1
 
6.7%
ü 1
 
6.7%
é 1
 
6.7%
1
 
6.7%
Hiragana
ValueCountFrequency (%)
2
33.3%
2
33.3%
2
33.3%
CJK
ValueCountFrequency (%)
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
1
 
6.2%
Other values (6) 6
37.5%
Punctuation
ValueCountFrequency (%)
1
100.0%

location
Text

Missing 

Distinct4127
Distinct (%)31.6%
Missing7287
Missing (%)35.8%
Memory size1.1 MiB
2024-11-22T22:04:15.991040image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length189
Median length77
Mean length12.347334
Min length1

Characters and Unicode

Total characters161392
Distinct characters321
Distinct categories20 ?
Distinct scripts10 ?
Distinct blocks21 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2972 ?
Unique (%)22.7%

Sample

1st rowZhuHai,China,Earth
2nd rowSussex, UK
3rd rowAustria
4th rowYokohama, Japan
5th rowLondon, UK
ValueCountFrequency (%)
germany 757
 
3.1%
ca 479
 
2.0%
china 434
 
1.8%
usa 414
 
1.7%
san 388
 
1.6%
uk 382
 
1.6%
france 377
 
1.5%
new 358
 
1.5%
wa 358
 
1.5%
canada 327
 
1.3%
Other values (3079) 20103
82.5%
2024-11-22T22:04:16.592154image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 15829
 
9.8%
n 12644
 
7.8%
e 11619
 
7.2%
11387
 
7.1%
i 8948
 
5.5%
r 8876
 
5.5%
o 8373
 
5.2%
, 7255
 
4.5%
l 5885
 
3.6%
t 5877
 
3.6%
Other values (311) 64699
40.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 112751
69.9%
Uppercase Letter 28055
 
17.4%
Space Separator 11389
 
7.1%
Other Punctuation 7911
 
4.9%
Decimal Number 496
 
0.3%
Dash Punctuation 228
 
0.1%
Other Letter 220
 
0.1%
Close Punctuation 94
 
0.1%
Open Punctuation 94
 
0.1%
Math Symbol 56
 
< 0.1%
Other values (10) 98
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
13
 
5.9%
8
 
3.6%
8
 
3.6%
7
 
3.2%
6
 
2.7%
6
 
2.7%
6
 
2.7%
6
 
2.7%
5
 
2.3%
5
 
2.3%
Other values (98) 150
68.2%
Lowercase Letter
ValueCountFrequency (%)
a 15829
14.0%
n 12644
11.2%
e 11619
10.3%
i 8948
 
7.9%
r 8876
 
7.9%
o 8373
 
7.4%
l 5885
 
5.2%
t 5877
 
5.2%
d 4542
 
4.0%
s 4449
 
3.9%
Other values (73) 25709
22.8%
Uppercase Letter
ValueCountFrequency (%)
S 3061
 
10.9%
A 2944
 
10.5%
C 2894
 
10.3%
B 1858
 
6.6%
N 1617
 
5.8%
U 1427
 
5.1%
M 1263
 
4.5%
G 1189
 
4.2%
P 1174
 
4.2%
T 1093
 
3.9%
Other values (30) 9535
34.0%
Other Punctuation
ValueCountFrequency (%)
, 7255
91.7%
. 260
 
3.3%
/ 223
 
2.8%
: 57
 
0.7%
' 44
 
0.6%
@ 12
 
0.2%
? 11
 
0.1%
! 8
 
0.1%
& 8
 
0.1%
6
 
0.1%
Other values (9) 27
 
0.3%
Other Symbol
ValueCountFrequency (%)
° 16
39.0%
3
 
7.3%
3
 
7.3%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
1
 
2.4%
1
 
2.4%
1
 
2.4%
Other values (8) 8
19.5%
Nonspacing Mark
ValueCountFrequency (%)
̶ 6
17.6%
5
14.7%
5
14.7%
4
11.8%
3
8.8%
3
8.8%
2
 
5.9%
2
 
5.9%
2
 
5.9%
1
 
2.9%
Decimal Number
ValueCountFrequency (%)
1 106
21.4%
0 90
18.1%
2 67
13.5%
3 45
9.1%
7 41
 
8.3%
6 32
 
6.5%
8 31
 
6.2%
5 30
 
6.0%
4 28
 
5.6%
9 26
 
5.2%
Math Symbol
ValueCountFrequency (%)
+ 17
30.4%
| 14
25.0%
> 11
19.6%
< 6
 
10.7%
~ 4
 
7.1%
= 1
 
1.8%
1
 
1.8%
1
 
1.8%
1
 
1.8%
Modifier Symbol
ValueCountFrequency (%)
` 4
44.4%
¯ 2
22.2%
¸ 2
22.2%
^ 1
 
11.1%
Dash Punctuation
ValueCountFrequency (%)
- 226
99.1%
1
 
0.4%
1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 86
91.5%
] 5
 
5.3%
} 3
 
3.2%
Open Punctuation
ValueCountFrequency (%)
( 86
91.5%
[ 5
 
5.3%
{ 3
 
3.2%
Space Separator
ValueCountFrequency (%)
11387
> 99.9%
  2
 
< 0.1%
Currency Symbol
ValueCountFrequency (%)
$ 3
75.0%
1
 
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Spacing Mark
ValueCountFrequency (%)
2
100.0%
Modifier Letter
ValueCountFrequency (%)
1
100.0%
Format
ValueCountFrequency (%)
1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 140744
87.2%
Common 20330
 
12.6%
Thai 126
 
0.1%
Han 92
 
0.1%
Cyrillic 60
 
< 0.1%
Katakana 14
 
< 0.1%
Inherited 11
 
< 0.1%
Devanagari 8
 
< 0.1%
Hiragana 5
 
< 0.1%
Greek 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 15829
 
11.2%
n 12644
 
9.0%
e 11619
 
8.3%
i 8948
 
6.4%
r 8876
 
6.3%
o 8373
 
5.9%
l 5885
 
4.2%
t 5877
 
4.2%
d 4542
 
3.2%
s 4449
 
3.2%
Other values (90) 53702
38.2%
Common
ValueCountFrequency (%)
11387
56.0%
, 7255
35.7%
. 260
 
1.3%
- 226
 
1.1%
/ 223
 
1.1%
1 106
 
0.5%
0 90
 
0.4%
) 86
 
0.4%
( 86
 
0.4%
2 67
 
0.3%
Other values (68) 544
 
2.7%
Han
ValueCountFrequency (%)
8
 
8.7%
7
 
7.6%
6
 
6.5%
6
 
6.5%
6
 
6.5%
4
 
4.3%
2
 
2.2%
2
 
2.2%
2
 
2.2%
2
 
2.2%
Other values (43) 47
51.1%
Thai
ValueCountFrequency (%)
13
 
10.3%
8
 
6.3%
6
 
4.8%
5
 
4.0%
5
 
4.0%
5
 
4.0%
5
 
4.0%
4
 
3.2%
4
 
3.2%
4
 
3.2%
Other values (31) 67
53.2%
Cyrillic
ValueCountFrequency (%)
с 9
15.0%
а 7
11.7%
о 7
11.7%
к 6
10.0%
и 5
8.3%
в 4
 
6.7%
р 4
 
6.7%
н 2
 
3.3%
б 2
 
3.3%
Н 2
 
3.3%
Other values (11) 12
20.0%
Katakana
ValueCountFrequency (%)
2
14.3%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Other values (3) 3
21.4%
Devanagari
ValueCountFrequency (%)
2
25.0%
2
25.0%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Hiragana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Inherited
ValueCountFrequency (%)
̶ 6
54.5%
5
45.5%
Greek
ValueCountFrequency (%)
ε 1
50.0%
α 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 160598
99.5%
None 428
 
0.3%
Thai 126
 
0.1%
CJK 92
 
0.1%
Cyrillic 60
 
< 0.1%
Katakana 15
 
< 0.1%
Punctuation 14
 
< 0.1%
Misc Symbols 10
 
< 0.1%
Devanagari 8
 
< 0.1%
Arrows 7
 
< 0.1%
Other values (11) 34
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 15829
 
9.9%
n 12644
 
7.9%
e 11619
 
7.2%
11387
 
7.1%
i 8948
 
5.6%
r 8876
 
5.5%
o 8373
 
5.2%
, 7255
 
4.5%
l 5885
 
3.7%
t 5877
 
3.7%
Other values (84) 63905
39.8%
None
ValueCountFrequency (%)
ü 77
18.0%
é 59
13.8%
ó 48
11.2%
ń 27
 
6.3%
ł 24
 
5.6%
ã 23
 
5.4%
ö 20
 
4.7%
á 18
 
4.2%
í 16
 
3.7%
° 16
 
3.7%
Other values (41) 100
23.4%
Thai
ValueCountFrequency (%)
13
 
10.3%
8
 
6.3%
6
 
4.8%
5
 
4.0%
5
 
4.0%
5
 
4.0%
5
 
4.0%
4
 
3.2%
4
 
3.2%
4
 
3.2%
Other values (31) 67
53.2%
Cyrillic
ValueCountFrequency (%)
с 9
15.0%
а 7
11.7%
о 7
11.7%
к 6
10.0%
и 5
8.3%
в 4
 
6.7%
р 4
 
6.7%
н 2
 
3.3%
б 2
 
3.3%
Н 2
 
3.3%
Other values (11) 12
20.0%
CJK
ValueCountFrequency (%)
8
 
8.7%
7
 
7.6%
6
 
6.5%
6
 
6.5%
6
 
6.5%
4
 
4.3%
2
 
2.2%
2
 
2.2%
2
 
2.2%
2
 
2.2%
Other values (43) 47
51.1%
Punctuation
ValueCountFrequency (%)
6
42.9%
2
 
14.3%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
1
 
7.1%
Diacriticals
ValueCountFrequency (%)
̶ 6
100.0%
VS
ValueCountFrequency (%)
5
100.0%
Dingbats
ValueCountFrequency (%)
3
100.0%
Misc Symbols
ValueCountFrequency (%)
3
30.0%
2
20.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
1
 
10.0%
Katakana
ValueCountFrequency (%)
2
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Other values (4) 4
26.7%
Devanagari
ValueCountFrequency (%)
2
25.0%
2
25.0%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Arrows
ValueCountFrequency (%)
2
28.6%
2
28.6%
1
14.3%
1
14.3%
1
14.3%
Latin Ext Additional
ValueCountFrequency (%)
2
33.3%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Misc Technical
ValueCountFrequency (%)
2
100.0%
Box Drawing
ValueCountFrequency (%)
1
100.0%
Hiragana
ValueCountFrequency (%)
1
20.0%
1
20.0%
1
20.0%
1
20.0%
1
20.0%
Math Operators
ValueCountFrequency (%)
1
50.0%
1
50.0%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Currency Symbols
ValueCountFrequency (%)
1
100.0%
Geometric Shapes
ValueCountFrequency (%)
1
50.0%
1
50.0%

email
Text

Missing 

Distinct8029
Distinct (%)97.0%
Missing12079
Missing (%)59.3%
Memory size1003.9 KiB
2024-11-22T22:04:16.886049image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length54
Median length39
Mean length20.460563
Min length7

Characters and Unicode

Total characters169393
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7779 ?
Unique (%)94.0%

Sample

1st rowhello@buddyspencer.monster
2nd rowatsushi@moongift.jp
3rd rowarthurdanjou@outlook.fr
4th rowshivsingh7150@hotmail.com
5th rowsovit.tamrakar@gmail.com
ValueCountFrequency (%)
h@tunius.se 2
 
< 0.1%
michael@herrmann.io 2
 
< 0.1%
ssisil@pivotal.io 2
 
< 0.1%
tony@bakeyournoodle.com 2
 
< 0.1%
bramleyjl@gmail.com 2
 
< 0.1%
angelo.zerr@gmail.com 2
 
< 0.1%
siddhartharramesh@gmail.com 2
 
< 0.1%
nihal@nihalgonsalves.com 2
 
< 0.1%
coletdjnz@proton.me 2
 
< 0.1%
karthik.s@harness.io 2
 
< 0.1%
Other values (8023) 8263
99.8%
2024-11-22T22:04:17.328199image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 14785
 
8.7%
o 14317
 
8.5%
m 13733
 
8.1%
i 11836
 
7.0%
. 11027
 
6.5%
e 10191
 
6.0%
c 9964
 
5.9%
l 9143
 
5.4%
@ 8278
 
4.9%
n 7638
 
4.5%
Other values (61) 58481
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 145930
86.1%
Other Punctuation 19309
 
11.4%
Decimal Number 3501
 
2.1%
Uppercase Letter 312
 
0.2%
Dash Punctuation 217
 
0.1%
Math Symbol 61
 
< 0.1%
Connector Punctuation 59
 
< 0.1%
Space Separator 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 14785
 
10.1%
o 14317
 
9.8%
m 13733
 
9.4%
i 11836
 
8.1%
e 10191
 
7.0%
c 9964
 
6.8%
l 9143
 
6.3%
n 7638
 
5.2%
r 7433
 
5.1%
g 6565
 
4.5%
Other values (16) 40325
27.6%
Uppercase Letter
ValueCountFrequency (%)
S 31
 
9.9%
A 29
 
9.3%
J 27
 
8.7%
M 25
 
8.0%
I 22
 
7.1%
P 15
 
4.8%
H 14
 
4.5%
G 13
 
4.2%
K 13
 
4.2%
T 12
 
3.8%
Other values (16) 111
35.6%
Decimal Number
ValueCountFrequency (%)
1 590
16.9%
0 503
14.4%
2 490
14.0%
9 386
11.0%
3 341
9.7%
6 260
7.4%
8 250
7.1%
4 245
7.0%
7 227
 
6.5%
5 209
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 11027
57.1%
@ 8278
42.9%
/ 3
 
< 0.1%
, 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+ 59
96.7%
| 2
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 217
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 59
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 146242
86.3%
Common 23151
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 14785
 
10.1%
o 14317
 
9.8%
m 13733
 
9.4%
i 11836
 
8.1%
e 10191
 
7.0%
c 9964
 
6.8%
l 9143
 
6.3%
n 7638
 
5.2%
r 7433
 
5.1%
g 6565
 
4.5%
Other values (42) 40637
27.8%
Common
ValueCountFrequency (%)
. 11027
47.6%
@ 8278
35.8%
1 590
 
2.5%
0 503
 
2.2%
2 490
 
2.1%
9 386
 
1.7%
3 341
 
1.5%
6 260
 
1.1%
8 250
 
1.1%
4 245
 
1.1%
Other values (9) 781
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 169393
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 14785
 
8.7%
o 14317
 
8.5%
m 13733
 
8.1%
i 11836
 
7.0%
. 11027
 
6.5%
e 10191
 
6.0%
c 9964
 
5.9%
l 9143
 
5.4%
@ 8278
 
4.9%
n 7638
 
4.5%
Other values (61) 58481
34.5%

hireable
Boolean

Constant  Missing 

Distinct1
Distinct (%)< 0.1%
Missing16956
Missing (%)83.3%
Memory size649.6 KiB
True
3402 
(Missing)
16956 
ValueCountFrequency (%)
True 3402
 
16.7%
(Missing) 16956
83.3%
2024-11-22T22:04:17.487991image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

bio
Text

Missing 

Distinct8641
Distinct (%)95.0%
Missing11262
Missing (%)55.3%
Memory size1.6 MiB
2024-11-22T22:04:17.831506image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length160
Median length116
Mean length61.902265
Min length1

Characters and Unicode

Total characters563063
Distinct characters1747
Distinct categories23 ?
Distinct scripts18 ?
Distinct blocks45 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8323 ?
Unique (%)91.5%

Sample

1st rowI just press the buttons randomly, and the program evolves...
2nd rowTime is unimportant, only life important.
3rd rowDone studying. Need challenges.
4th rowAdministrator of MOONGIFT that is introducing open source software everyday to Japanese engineers since 2004.
5th rowSenior Software Engineer at Google, working on Certificate Transparency and generalized transparency.
ValueCountFrequency (%)
3159
 
3.9%
and 2613
 
3.2%
engineer 1634
 
2.0%
software 1575
 
2.0%
of 1527
 
1.9%
at 1427
 
1.8%
developer 1275
 
1.6%
the 1112
 
1.4%
i 1069
 
1.3%
a 1056
 
1.3%
Other values (14754) 64292
79.6%
2024-11-22T22:04:18.479236image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72137
 
12.8%
e 51177
 
9.1%
o 33355
 
5.9%
n 32396
 
5.8%
a 32307
 
5.7%
t 32177
 
5.7%
r 32161
 
5.7%
i 29413
 
5.2%
s 20263
 
3.6%
l 15230
 
2.7%
Other values (1737) 212447
37.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 400648
71.2%
Space Separator 72320
 
12.8%
Uppercase Letter 45150
 
8.0%
Other Punctuation 24510
 
4.4%
Control 6034
 
1.1%
Decimal Number 3662
 
0.7%
Dash Punctuation 2636
 
0.5%
Other Letter 2048
 
0.4%
Other Symbol 2045
 
0.4%
Math Symbol 1798
 
0.3%
Other values (13) 2212
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
26
 
1.3%
20
 
1.0%
20
 
1.0%
14
 
0.7%
13
 
0.6%
13
 
0.6%
12
 
0.6%
12
 
0.6%
12
 
0.6%
11
 
0.5%
Other values (912) 1895
92.5%
Other Symbol
ValueCountFrequency (%)
141
 
6.9%
💻 86
 
4.2%
🍕 81
 
4.0%
73
 
3.6%
62
 
3.0%
59
 
2.9%
👨 58
 
2.8%
🚀 46
 
2.2%
🐁 39
 
1.9%
39
 
1.9%
Other values (429) 1361
66.6%
Lowercase Letter
ValueCountFrequency (%)
e 51177
12.8%
o 33355
 
8.3%
n 32396
 
8.1%
a 32307
 
8.1%
t 32177
 
8.0%
r 32161
 
8.0%
i 29413
 
7.3%
s 20263
 
5.1%
l 15230
 
3.8%
c 14670
 
3.7%
Other values (137) 107499
26.8%
Nonspacing Mark
ValueCountFrequency (%)
208
61.2%
̶ 10
 
2.9%
̭ 6
 
1.8%
̯ 6
 
1.8%
͡ 6
 
1.8%
͉ 6
 
1.8%
́ 5
 
1.5%
̘ 4
 
1.2%
̩ 4
 
1.2%
̪ 4
 
1.2%
Other values (45) 81
 
23.8%
Uppercase Letter
ValueCountFrequency (%)
S 5883
13.0%
C 3937
 
8.7%
E 3107
 
6.9%
I 3013
 
6.7%
P 2930
 
6.5%
D 2826
 
6.3%
A 2825
 
6.3%
M 2410
 
5.3%
T 2175
 
4.8%
F 1803
 
4.0%
Other values (34) 14241
31.5%
Other Punctuation
ValueCountFrequency (%)
. 7917
32.3%
, 6115
24.9%
@ 4308
17.6%
/ 2070
 
8.4%
: 893
 
3.6%
' 768
 
3.1%
& 685
 
2.8%
! 393
 
1.6%
# 323
 
1.3%
; 231
 
0.9%
Other values (24) 807
 
3.3%
Math Symbol
ValueCountFrequency (%)
| 1166
64.8%
+ 421
 
23.4%
> 72
 
4.0%
= 46
 
2.6%
< 39
 
2.2%
~ 26
 
1.4%
8
 
0.4%
4
 
0.2%
3
 
0.2%
2
 
0.1%
Other values (10) 11
 
0.6%
Decimal Number
ValueCountFrequency (%)
2 675
18.4%
0 605
16.5%
1 593
16.2%
3 375
10.2%
9 281
7.7%
8 247
 
6.7%
6 241
 
6.6%
4 233
 
6.4%
5 221
 
6.0%
7 187
 
5.1%
Other values (3) 4
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 587
85.1%
] 58
 
8.4%
} 20
 
2.9%
9
 
1.3%
5
 
0.7%
4
 
0.6%
3
 
0.4%
2
 
0.3%
1
 
0.1%
1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 552
85.1%
[ 57
 
8.8%
{ 22
 
3.4%
7
 
1.1%
3
 
0.5%
2
 
0.3%
2
 
0.3%
2
 
0.3%
1
 
0.2%
1
 
0.2%
Modifier Symbol
ValueCountFrequency (%)
🏻 30
31.6%
` 20
21.1%
¯ 18
18.9%
🏽 10
 
10.5%
🏼 9
 
9.5%
🏾 3
 
3.2%
^ 3
 
3.2%
2
 
2.1%
Private Use
ValueCountFrequency (%)
6
40.0%
2
 
13.3%
2
 
13.3%
2
 
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Space Separator
ValueCountFrequency (%)
72137
99.7%
  61
 
0.1%
48
 
0.1%
  45
 
0.1%
27
 
< 0.1%
2
 
< 0.1%
Modifier Letter
ValueCountFrequency (%)
10
62.5%
ˌ 2
 
12.5%
ˈ 2
 
12.5%
ː 1
 
6.2%
1
 
6.2%
Other Number
ValueCountFrequency (%)
² 2
33.3%
1
16.7%
¼ 1
16.7%
¹ 1
16.7%
1
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 2586
98.1%
31
 
1.2%
18
 
0.7%
1
 
< 0.1%
Format
ValueCountFrequency (%)
143
96.6%
2
 
1.4%
­ 2
 
1.4%
1
 
0.7%
Final Punctuation
ValueCountFrequency (%)
31
60.8%
15
29.4%
» 5
 
9.8%
Currency Symbol
ValueCountFrequency (%)
$ 15
71.4%
5
 
23.8%
£ 1
 
4.8%
Initial Punctuation
ValueCountFrequency (%)
13
72.2%
4
 
22.2%
« 1
 
5.6%
Control
ValueCountFrequency (%)
3017
50.0%
3017
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 157
96.9%
5
 
3.1%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 445506
79.1%
Common 114738
 
20.4%
Han 1541
 
0.3%
Inherited 483
 
0.1%
Cyrillic 244
 
< 0.1%
Hangul 174
 
< 0.1%
Hiragana 166
 
< 0.1%
Katakana 80
 
< 0.1%
Arabic 67
 
< 0.1%
Greek 26
 
< 0.1%
Other values (8) 38
 
< 0.1%

Most frequent character per script

Han
ValueCountFrequency (%)
26
 
1.7%
20
 
1.3%
20
 
1.3%
14
 
0.9%
13
 
0.8%
13
 
0.8%
12
 
0.8%
11
 
0.7%
11
 
0.7%
11
 
0.7%
Other values (680) 1390
90.2%
Common
ValueCountFrequency (%)
72137
62.9%
. 7917
 
6.9%
, 6115
 
5.3%
@ 4308
 
3.8%
3017
 
2.6%
3017
 
2.6%
- 2586
 
2.3%
/ 2070
 
1.8%
| 1166
 
1.0%
: 893
 
0.8%
Other values (575) 11512
 
10.0%
Latin
ValueCountFrequency (%)
e 51177
 
11.5%
o 33355
 
7.5%
n 32396
 
7.3%
a 32307
 
7.3%
t 32177
 
7.2%
r 32161
 
7.2%
i 29413
 
6.6%
s 20263
 
4.5%
l 15230
 
3.4%
c 14670
 
3.3%
Other values (107) 152357
34.2%
Hangul
ValueCountFrequency (%)
8
 
4.6%
7
 
4.0%
7
 
4.0%
5
 
2.9%
4
 
2.3%
4
 
2.3%
4
 
2.3%
4
 
2.3%
4
 
2.3%
3
 
1.7%
Other values (102) 124
71.3%
Inherited
ValueCountFrequency (%)
208
43.1%
143
29.6%
̶ 10
 
2.1%
̭ 6
 
1.2%
̯ 6
 
1.2%
͡ 6
 
1.2%
͉ 6
 
1.2%
́ 5
 
1.0%
̘ 4
 
0.8%
̩ 4
 
0.8%
Other values (46) 85
17.6%
Katakana
ValueCountFrequency (%)
11
 
13.8%
4
 
5.0%
4
 
5.0%
3
 
3.8%
3
 
3.8%
3
 
3.8%
3
 
3.8%
3
 
3.8%
3
 
3.8%
2
 
2.5%
Other values (32) 41
51.2%
Cyrillic
ValueCountFrequency (%)
а 27
 
11.1%
т 18
 
7.4%
о 18
 
7.4%
н 14
 
5.7%
е 13
 
5.3%
в 12
 
4.9%
и 12
 
4.9%
с 11
 
4.5%
у 9
 
3.7%
р 8
 
3.3%
Other values (31) 102
41.8%
Hiragana
ValueCountFrequency (%)
12
 
7.2%
12
 
7.2%
9
 
5.4%
8
 
4.8%
8
 
4.8%
7
 
4.2%
7
 
4.2%
7
 
4.2%
7
 
4.2%
7
 
4.2%
Other values (30) 82
49.4%
Arabic
ValueCountFrequency (%)
ا 10
14.9%
م 8
11.9%
و 7
10.4%
ت 6
 
9.0%
ل 5
 
7.5%
ر 4
 
6.0%
ع 4
 
6.0%
ة 3
 
4.5%
ي 3
 
4.5%
ح 2
 
3.0%
Other values (12) 15
22.4%
Greek
ValueCountFrequency (%)
ω 4
15.4%
λ 3
11.5%
π 2
 
7.7%
θ 2
 
7.7%
ς 2
 
7.7%
ρ 2
 
7.7%
η 1
 
3.8%
ν 1
 
3.8%
ά 1
 
3.8%
ι 1
 
3.8%
Other values (7) 7
26.9%
Hebrew
ValueCountFrequency (%)
מ 2
14.3%
ר 2
14.3%
ש 2
14.3%
ח 1
7.1%
ה 1
7.1%
ע 1
7.1%
ם 1
7.1%
י 1
7.1%
ו 1
7.1%
א 1
7.1%
Unknown
ValueCountFrequency (%)
6
40.0%
2
 
13.3%
2
 
13.3%
2
 
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Tibetan
ValueCountFrequency (%)
1
50.0%
1
50.0%
Thai
ValueCountFrequency (%)
2
100.0%
Kannada
ValueCountFrequency (%)
2
100.0%
Egyptian_Hieroglyphs
ValueCountFrequency (%)
𓀡 1
100.0%
Mandaic
ValueCountFrequency (%)
1
100.0%
Devanagari
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 556997
98.9%
None 1865
 
0.3%
CJK 1541
 
0.3%
Punctuation 585
 
0.1%
Block Elements 255
 
< 0.1%
Cyrillic 244
 
< 0.1%
VS 209
 
< 0.1%
Enclosed Alphanum Sup 183
 
< 0.1%
Hiragana 166
 
< 0.1%
Hangul 165
 
< 0.1%
Other values (35) 853
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72137
 
13.0%
e 51177
 
9.2%
o 33355
 
6.0%
n 32396
 
5.8%
a 32307
 
5.8%
t 32177
 
5.8%
r 32161
 
5.8%
i 29413
 
5.3%
s 20263
 
3.6%
l 15230
 
2.7%
Other values (87) 206381
37.1%
Punctuation
ValueCountFrequency (%)
224
38.3%
143
24.4%
48
 
8.2%
31
 
5.3%
31
 
5.3%
27
 
4.6%
18
 
3.1%
15
 
2.6%
13
 
2.2%
12
 
2.1%
Other values (10) 23
 
3.9%
VS
ValueCountFrequency (%)
208
99.5%
1
 
0.5%
Block Elements
ValueCountFrequency (%)
141
55.3%
62
24.3%
39
 
15.3%
11
 
4.3%
1
 
0.4%
1
 
0.4%
None
ValueCountFrequency (%)
💻 86
 
4.6%
🍕 81
 
4.3%
73
 
3.9%
  61
 
3.3%
👨 58
 
3.1%
57
 
3.1%
· 54
 
2.9%
🚀 46
 
2.5%
  45
 
2.4%
🐁 39
 
2.1%
Other values (407) 1265
67.8%
Dingbats
ValueCountFrequency (%)
73
44.8%
59
36.2%
5
 
3.1%
5
 
3.1%
3
 
1.8%
2
 
1.2%
2
 
1.2%
2
 
1.2%
1
 
0.6%
1
 
0.6%
Other values (10) 10
 
6.1%
Misc Symbols
ValueCountFrequency (%)
31
22.1%
22
15.7%
14
10.0%
12
 
8.6%
9
 
6.4%
5
 
3.6%
4
 
2.9%
4
 
2.9%
3
 
2.1%
3
 
2.1%
Other values (24) 33
23.6%
Enclosed Alphanum Sup
ValueCountFrequency (%)
🇦 31
16.9%
🇺 29
15.8%
🇧 18
9.8%
🇷 16
8.7%
🇨 15
8.2%
🇬 11
 
6.0%
🇸 8
 
4.4%
🇪 8
 
4.4%
🇹 6
 
3.3%
🇮 6
 
3.3%
Other values (13) 35
19.1%
Cyrillic
ValueCountFrequency (%)
а 27
 
11.1%
т 18
 
7.4%
о 18
 
7.4%
н 14
 
5.7%
е 13
 
5.3%
в 12
 
4.9%
и 12
 
4.9%
с 11
 
4.5%
у 9
 
3.7%
р 8
 
3.3%
Other values (31) 102
41.8%
CJK
ValueCountFrequency (%)
26
 
1.7%
20
 
1.3%
20
 
1.3%
14
 
0.9%
13
 
0.8%
13
 
0.8%
12
 
0.8%
11
 
0.7%
11
 
0.7%
11
 
0.7%
Other values (680) 1390
90.2%
Hiragana
ValueCountFrequency (%)
12
 
7.2%
12
 
7.2%
9
 
5.4%
8
 
4.8%
8
 
4.8%
7
 
4.2%
7
 
4.2%
7
 
4.2%
7
 
4.2%
7
 
4.2%
Other values (30) 82
49.4%
Katakana
ValueCountFrequency (%)
11
 
12.9%
10
 
11.8%
5
 
5.9%
4
 
4.7%
4
 
4.7%
3
 
3.5%
3
 
3.5%
3
 
3.5%
3
 
3.5%
3
 
3.5%
Other values (27) 36
42.4%
Diacriticals
ValueCountFrequency (%)
̶ 10
 
7.8%
̭ 6
 
4.7%
̯ 6
 
4.7%
͡ 6
 
4.7%
͉ 6
 
4.7%
́ 5
 
3.9%
̘ 4
 
3.1%
̩ 4
 
3.1%
̪ 4
 
3.1%
͜ 4
 
3.1%
Other values (40) 73
57.0%
Arabic
ValueCountFrequency (%)
ا 10
14.7%
م 8
11.8%
و 7
10.3%
ت 6
 
8.8%
ل 5
 
7.4%
ر 4
 
5.9%
ع 4
 
5.9%
ة 3
 
4.4%
ي 3
 
4.4%
ح 2
 
2.9%
Other values (13) 16
23.5%
Arrows
ValueCountFrequency (%)
8
53.3%
4
26.7%
3
 
20.0%
Emoticons
ValueCountFrequency (%)
🙈 8
 
12.5%
🙉 6
 
9.4%
🙂 5
 
7.8%
😄 4
 
6.2%
🙋 3
 
4.7%
😜 3
 
4.7%
😃 3
 
4.7%
😎 3
 
4.7%
😉 2
 
3.1%
😁 2
 
3.1%
Other values (18) 25
39.1%
Geometric Shapes Ext
ValueCountFrequency (%)
🟦 8
57.1%
🟨 6
42.9%
Compat Jamo
ValueCountFrequency (%)
8
100.0%
Hangul
ValueCountFrequency (%)
7
 
4.2%
7
 
4.2%
5
 
3.0%
4
 
2.4%
4
 
2.4%
4
 
2.4%
4
 
2.4%
4
 
2.4%
3
 
1.8%
3
 
1.8%
Other values (100) 120
72.7%
Geometric Shapes
ValueCountFrequency (%)
6
31.6%
2
 
10.5%
2
 
10.5%
2
 
10.5%
2
 
10.5%
2
 
10.5%
1
 
5.3%
1
 
5.3%
1
 
5.3%
Letterlike Symbols
ValueCountFrequency (%)
6
100.0%
PUA
ValueCountFrequency (%)
6
40.0%
2
 
13.3%
2
 
13.3%
2
 
13.3%
1
 
6.7%
1
 
6.7%
1
 
6.7%
Box Drawing
ValueCountFrequency (%)
6
28.6%
6
28.6%
5
23.8%
3
14.3%
1
 
4.8%
Currency Symbols
ValueCountFrequency (%)
5
100.0%
Sup Punctuation
ValueCountFrequency (%)
4
100.0%
Math Operators
ValueCountFrequency (%)
3
23.1%
2
15.4%
2
15.4%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
1
 
7.7%
Thai
ValueCountFrequency (%)
2
100.0%
Phonetic Ext
ValueCountFrequency (%)
2
33.3%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Math Alphanum
ValueCountFrequency (%)
𝘴 2
 
8.3%
𝘭 2
 
8.3%
𝘶 2
 
8.3%
𝘵 2
 
8.3%
𝒽 1
 
4.2%
𝒾 1
 
4.2%
𝐂 1
 
4.2%
𝐑 1
 
4.2%
𝟎 1
 
4.2%
𝟖 1
 
4.2%
Other values (10) 10
41.7%
Kannada
ValueCountFrequency (%)
2
100.0%
Modifier Letters
ValueCountFrequency (%)
ˌ 2
40.0%
ˈ 2
40.0%
ː 1
20.0%
IPA Ext
ValueCountFrequency (%)
ʖ 2
20.0%
ʔ 1
10.0%
ʕ 1
10.0%
ɴ 1
10.0%
ʀ 1
10.0%
ɛ 1
10.0%
ɹ 1
10.0%
ɾ 1
10.0%
ɚ 1
10.0%
Misc Technical
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
CJK Compat Forms
ValueCountFrequency (%)
2
100.0%
Hebrew
ValueCountFrequency (%)
מ 2
14.3%
ר 2
14.3%
ש 2
14.3%
ח 1
7.1%
ה 1
7.1%
ע 1
7.1%
ם 1
7.1%
י 1
7.1%
ו 1
7.1%
א 1
7.1%
Jamo
ValueCountFrequency (%)
1
100.0%
Latin Ext Additional
ValueCountFrequency (%)
1
50.0%
1
50.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
Egyptian Hieroglyphs
ValueCountFrequency (%)
𓀡 1
100.0%
Mahjong
ValueCountFrequency (%)
🀄 1
100.0%
Diacriticals Sup
ValueCountFrequency (%)
1
50.0%
1
50.0%
Mandaic
ValueCountFrequency (%)
1
100.0%
Devanagari
ValueCountFrequency (%)
1
100.0%
Tibetan
ValueCountFrequency (%)
1
50.0%
1
50.0%
Enclosed Alphanum
ValueCountFrequency (%)
1
100.0%

twitter_username
Text

Missing 

Distinct4912
Distinct (%)97.1%
Missing15297
Missing (%)75.1%
Memory size808.2 KiB
2024-11-22T22:04:18.797207image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length15
Median length11
Mean length9.7733649
Min length2

Characters and Unicode

Total characters49463
Distinct characters63
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4763 ?
Unique (%)94.1%

Sample

1st rowzoomq
2nd rowBuddySp3nc3r
3rd rowjamiesheep
4th rowGaelJourdanWeil
5th rowhalbecaf
ValueCountFrequency (%)
schamschula 2
 
< 0.1%
m_herrmann 2
 
< 0.1%
ybiquitous 2
 
< 0.1%
angelozerr 2
 
< 0.1%
sagikazarmark 2
 
< 0.1%
mariatta 2
 
< 0.1%
mergifyio 2
 
< 0.1%
der0ad 2
 
< 0.1%
philwareham 2
 
< 0.1%
awscloud 2
 
< 0.1%
Other values (4902) 5041
99.6%
2024-11-22T22:04:19.292766image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4754
 
9.6%
e 4239
 
8.6%
i 3333
 
6.7%
r 3257
 
6.6%
n 3122
 
6.3%
o 2966
 
6.0%
s 2526
 
5.1%
l 2211
 
4.5%
t 2133
 
4.3%
h 1768
 
3.6%
Other values (53) 19154
38.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 44490
89.9%
Uppercase Letter 2199
 
4.4%
Decimal Number 1789
 
3.6%
Connector Punctuation 985
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4754
 
10.7%
e 4239
 
9.5%
i 3333
 
7.5%
r 3257
 
7.3%
n 3122
 
7.0%
o 2966
 
6.7%
s 2526
 
5.7%
l 2211
 
5.0%
t 2133
 
4.8%
h 1768
 
4.0%
Other values (16) 14181
31.9%
Uppercase Letter
ValueCountFrequency (%)
S 204
 
9.3%
M 189
 
8.6%
A 157
 
7.1%
T 143
 
6.5%
B 125
 
5.7%
D 122
 
5.5%
J 121
 
5.5%
C 106
 
4.8%
L 102
 
4.6%
P 98
 
4.5%
Other values (16) 832
37.8%
Decimal Number
ValueCountFrequency (%)
0 332
18.6%
1 330
18.4%
2 211
11.8%
9 172
9.6%
3 148
8.3%
7 134
7.5%
8 132
 
7.4%
4 127
 
7.1%
5 109
 
6.1%
6 94
 
5.3%
Connector Punctuation
ValueCountFrequency (%)
_ 985
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 46689
94.4%
Common 2774
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4754
 
10.2%
e 4239
 
9.1%
i 3333
 
7.1%
r 3257
 
7.0%
n 3122
 
6.7%
o 2966
 
6.4%
s 2526
 
5.4%
l 2211
 
4.7%
t 2133
 
4.6%
h 1768
 
3.8%
Other values (42) 16380
35.1%
Common
ValueCountFrequency (%)
_ 985
35.5%
0 332
 
12.0%
1 330
 
11.9%
2 211
 
7.6%
9 172
 
6.2%
3 148
 
5.3%
7 134
 
4.8%
8 132
 
4.8%
4 127
 
4.6%
5 109
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49463
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4754
 
9.6%
e 4239
 
8.6%
i 3333
 
6.7%
r 3257
 
6.6%
n 3122
 
6.3%
o 2966
 
6.0%
s 2526
 
5.1%
l 2211
 
4.5%
t 2133
 
4.3%
h 1768
 
3.6%
Other values (53) 19154
38.7%

public_repos
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct674
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.608066
Minimum0
Maximum50000
Zeros964
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size159.2 KiB
2024-11-22T22:04:19.486888image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q111
median35
Q383
95-th percentile249
Maximum50000
Range50000
Interquartile range (IQR)72

Descriptive statistics

Standard deviation566.6837
Coefficient of variation (CV)6.7778592
Kurtosis3802.1201
Mean83.608066
Median Absolute Deviation (MAD)29
Skewness54.593341
Sum1702093
Variance321130.41
MonotonicityNot monotonic
2024-11-22T22:04:19.666445image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 964
 
4.7%
1 574
 
2.8%
2 473
 
2.3%
3 404
 
2.0%
4 389
 
1.9%
6 377
 
1.9%
5 369
 
1.8%
7 345
 
1.7%
9 323
 
1.6%
8 313
 
1.5%
Other values (664) 15827
77.7%
ValueCountFrequency (%)
0 964
4.7%
1 574
2.8%
2 473
2.3%
3 404
2.0%
4 389
1.9%
5 369
 
1.8%
6 377
 
1.9%
7 345
 
1.7%
8 313
 
1.5%
9 323
 
1.6%
ValueCountFrequency (%)
50000 1
< 0.1%
27746 1
< 0.1%
26360 1
< 0.1%
22618 1
< 0.1%
20693 1
< 0.1%
17425 1
< 0.1%
16985 1
< 0.1%
16839 1
< 0.1%
9666 1
< 0.1%
9554 1
< 0.1%

public_gists
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct359
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.865753
Minimum0
Maximum55781
Zeros8176
Zeros (%)40.2%
Negative0
Negative (%)0.0%
Memory size159.2 KiB
2024-11-22T22:04:19.819343image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q310
95-th percentile66
Maximum55781
Range55781
Interquartile range (IQR)10

Descriptive statistics

Standard deviation626.46105
Coefficient of variation (CV)25.193729
Kurtosis6131.7796
Mean24.865753
Median Absolute Deviation (MAD)2
Skewness75.171577
Sum506217
Variance392453.44
MonotonicityNot monotonic
2024-11-22T22:04:19.981975image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8176
40.2%
1 1929
 
9.5%
2 1192
 
5.9%
3 844
 
4.1%
4 695
 
3.4%
5 643
 
3.2%
6 512
 
2.5%
7 418
 
2.1%
9 337
 
1.7%
8 328
 
1.6%
Other values (349) 5284
26.0%
ValueCountFrequency (%)
0 8176
40.2%
1 1929
 
9.5%
2 1192
 
5.9%
3 844
 
4.1%
4 695
 
3.4%
5 643
 
3.2%
6 512
 
2.5%
7 418
 
2.1%
8 328
 
1.6%
9 337
 
1.7%
ValueCountFrequency (%)
55781 1
< 0.1%
53660 1
< 0.1%
28943 1
< 0.1%
26879 1
< 0.1%
15482 1
< 0.1%
10604 1
< 0.1%
3450 1
< 0.1%
3170 1
< 0.1%
2565 1
< 0.1%
1750 1
< 0.1%

followers
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct1600
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean243.00943
Minimum0
Maximum95752
Zeros1476
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size159.2 KiB
2024-11-22T22:04:20.150538image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median33
Q3124
95-th percentile825.45
Maximum95752
Range95752
Interquartile range (IQR)117

Descriptive statistics

Standard deviation1520.847
Coefficient of variation (CV)6.2583869
Kurtosis1587.9428
Mean243.00943
Median Absolute Deviation (MAD)31
Skewness32.591042
Sum4947186
Variance2312975.7
MonotonicityNot monotonic
2024-11-22T22:04:20.316220image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1476
 
7.3%
1 822
 
4.0%
2 646
 
3.2%
3 534
 
2.6%
4 461
 
2.3%
5 423
 
2.1%
6 405
 
2.0%
7 356
 
1.7%
8 353
 
1.7%
9 322
 
1.6%
Other values (1590) 14560
71.5%
ValueCountFrequency (%)
0 1476
7.3%
1 822
4.0%
2 646
3.2%
3 534
 
2.6%
4 461
 
2.3%
5 423
 
2.1%
6 405
 
2.0%
7 356
 
1.7%
8 353
 
1.7%
9 322
 
1.6%
ValueCountFrequency (%)
95752 1
< 0.1%
84979 1
< 0.1%
66203 1
< 0.1%
58452 1
< 0.1%
31120 1
< 0.1%
30287 1
< 0.1%
29719 1
< 0.1%
29414 1
< 0.1%
28411 1
< 0.1%
25815 1
< 0.1%

following
Real number (ℝ)

High correlation  Skewed  Zeros 

Distinct620
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.250368
Minimum0
Maximum27775
Zeros6189
Zeros (%)30.4%
Negative0
Negative (%)0.0%
Memory size159.2 KiB
2024-11-22T22:04:20.474238image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q322
95-th percentile148.15
Maximum27775
Range27775
Interquartile range (IQR)22

Descriptive statistics

Standard deviation362.16041
Coefficient of variation (CV)8.1843478
Kurtosis2309.8615
Mean44.250368
Median Absolute Deviation (MAD)4
Skewness40.242606
Sum900849
Variance131160.16
MonotonicityNot monotonic
2024-11-22T22:04:20.639581image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6189
30.4%
1 1789
 
8.8%
2 1130
 
5.6%
3 820
 
4.0%
4 621
 
3.1%
5 549
 
2.7%
6 495
 
2.4%
7 417
 
2.0%
8 380
 
1.9%
9 328
 
1.6%
Other values (610) 7640
37.5%
ValueCountFrequency (%)
0 6189
30.4%
1 1789
 
8.8%
2 1130
 
5.6%
3 820
 
4.0%
4 621
 
3.1%
5 549
 
2.7%
6 495
 
2.4%
7 417
 
2.0%
8 380
 
1.9%
9 328
 
1.6%
ValueCountFrequency (%)
27775 1
< 0.1%
16741 1
< 0.1%
15931 1
< 0.1%
11921 1
< 0.1%
10268 1
< 0.1%
9720 1
< 0.1%
9686 1
< 0.1%
9532 1
< 0.1%
9367 1
< 0.1%
7374 1
< 0.1%
Distinct19767
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size159.2 KiB
Minimum2008-01-27 07:09:47+00:00
Maximum2021-12-20 05:29:41+00:00
2024-11-22T22:04:20.814690image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:21.015472image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct19638
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size159.2 KiB
Minimum2016-08-08 22:18:09+00:00
Maximum2023-10-14 14:33:48+00:00
2024-11-22T22:04:21.621149image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:21.804517image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2862
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size1.2 MiB
2024-11-22T22:04:22.166452image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.250221
Min length4

Characters and Unicode

Total characters127242
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1558 ?
Unique (%)7.7%

Sample

1st row500.00%
2nd row150.00%
3rd row548.00%
4th row4200.00%
5th row300.00%
ValueCountFrequency (%)
inf 4903
 
24.1%
0.00 1476
 
7.3%
100.00 386
 
1.9%
200.00 300
 
1.5%
300.00 222
 
1.1%
400.00 165
 
0.8%
600.00 129
 
0.6%
500.00 116
 
0.6%
700.00 110
 
0.5%
800.00 107
 
0.5%
Other values (2852) 12444
61.1%
2024-11-22T22:04:22.742025image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 42226
33.2%
% 20358
16.0%
. 15455
 
12.1%
1 6549
 
5.1%
i 4903
 
3.9%
n 4903
 
3.9%
f 4903
 
3.9%
2 4851
 
3.8%
3 4611
 
3.6%
5 4023
 
3.2%
Other values (5) 14460
 
11.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76720
60.3%
Other Punctuation 35813
28.1%
Lowercase Letter 14709
 
11.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 42226
55.0%
1 6549
 
8.5%
2 4851
 
6.3%
3 4611
 
6.0%
5 4023
 
5.2%
4 3257
 
4.2%
7 3216
 
4.2%
6 3172
 
4.1%
8 2762
 
3.6%
9 2053
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
i 4903
33.3%
n 4903
33.3%
f 4903
33.3%
Other Punctuation
ValueCountFrequency (%)
% 20358
56.8%
. 15455
43.2%

Most occurring scripts

ValueCountFrequency (%)
Common 112533
88.4%
Latin 14709
 
11.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 42226
37.5%
% 20358
18.1%
. 15455
 
13.7%
1 6549
 
5.8%
2 4851
 
4.3%
3 4611
 
4.1%
5 4023
 
3.6%
4 3257
 
2.9%
7 3216
 
2.9%
6 3172
 
2.8%
Other values (2) 4815
 
4.3%
Latin
ValueCountFrequency (%)
i 4903
33.3%
n 4903
33.3%
f 4903
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 127242
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 42226
33.2%
% 20358
16.0%
. 15455
 
12.1%
1 6549
 
5.1%
i 4903
 
3.9%
n 4903
 
3.9%
f 4903
 
3.9%
2 4851
 
3.8%
3 4611
 
3.6%
5 4023
 
3.2%
Other values (5) 14460
 
11.4%

log_public_repos
Real number (ℝ)

High correlation  Zeros 

Distinct674
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3932475
Minimum0
Maximum10.819798
Zeros964
Zeros (%)4.7%
Negative0
Negative (%)0.0%
Memory size159.2 KiB
2024-11-22T22:04:22.943294image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.69314718
Q12.4849066
median3.5835189
Q34.4308168
95-th percentile5.5214609
Maximum10.819798
Range10.819798
Interquartile range (IQR)1.9459101

Descriptive statistics

Standard deviation1.4780875
Coefficient of variation (CV)0.43559671
Kurtosis0.061349745
Mean3.3932475
Median Absolute Deviation (MAD)0.94446161
Skewness-0.38450162
Sum69079.734
Variance2.1847426
MonotonicityNot monotonic
2024-11-22T22:04:23.142414image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 964
 
4.7%
0.6931471806 574
 
2.8%
1.098612289 473
 
2.3%
1.386294361 404
 
2.0%
1.609437912 389
 
1.9%
1.945910149 377
 
1.9%
1.791759469 369
 
1.8%
2.079441542 345
 
1.7%
2.302585093 323
 
1.6%
2.197224577 313
 
1.5%
Other values (664) 15827
77.7%
ValueCountFrequency (%)
0 964
4.7%
0.6931471806 574
2.8%
1.098612289 473
2.3%
1.386294361 404
2.0%
1.609437912 389
1.9%
1.791759469 369
 
1.8%
1.945910149 377
 
1.9%
2.079441542 345
 
1.7%
2.197224577 313
 
1.5%
2.302585093 323
 
1.6%
ValueCountFrequency (%)
10.81979828 1
< 0.1%
10.23088301 1
< 0.1%
10.17964092 1
< 0.1%
10.02654554 1
< 0.1%
9.937599082 1
< 0.1%
9.765718623 1
< 0.1%
9.740144754 1
< 0.1%
9.731512288 1
< 0.1%
9.176473302 1
< 0.1%
9.164819857 1
< 0.1%

log_public_gists
Real number (ℝ)

High correlation  Zeros 

Distinct359
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3680664
Minimum0
Maximum10.929207
Zeros8176
Zeros (%)40.2%
Negative0
Negative (%)0.0%
Memory size159.2 KiB
2024-11-22T22:04:23.306507image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.0986123
Q32.3978953
95-th percentile4.2046926
Maximum10.929207
Range10.929207
Interquartile range (IQR)2.3978953

Descriptive statistics

Standard deviation1.491835
Coefficient of variation (CV)1.0904697
Kurtosis0.24735254
Mean1.3680664
Median Absolute Deviation (MAD)1.0986123
Skewness0.9258647
Sum27851.096
Variance2.2255716
MonotonicityNot monotonic
2024-11-22T22:04:23.466630image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8176
40.2%
0.6931471806 1929
 
9.5%
1.098612289 1192
 
5.9%
1.386294361 844
 
4.1%
1.609437912 695
 
3.4%
1.791759469 643
 
3.2%
1.945910149 512
 
2.5%
2.079441542 418
 
2.1%
2.302585093 337
 
1.7%
2.197224577 328
 
1.6%
Other values (349) 5284
26.0%
ValueCountFrequency (%)
0 8176
40.2%
0.6931471806 1929
 
9.5%
1.098612289 1192
 
5.9%
1.386294361 844
 
4.1%
1.609437912 695
 
3.4%
1.791759469 643
 
3.2%
1.945910149 512
 
2.5%
2.079441542 418
 
2.1%
2.197224577 328
 
1.6%
2.302585093 337
 
1.7%
ValueCountFrequency (%)
10.92920652 1
< 0.1%
10.89044176 1
< 0.1%
10.27311821 1
< 0.1%
10.19913779 1
< 0.1%
9.647497927 1
< 0.1%
9.269080867 1
< 0.1%
8.146419323 1
< 0.1%
8.061802275 1
< 0.1%
7.850103545 1
< 0.1%
7.467942332 1
< 0.1%

log_followers
Real number (ℝ)

High correlation  Zeros 

Distinct1600
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5022832
Minimum0
Maximum11.469527
Zeros1476
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size159.2 KiB
2024-11-22T22:04:23.631773image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.0794415
median3.5263605
Q34.8283137
95-th percentile6.7171386
Maximum11.469527
Range11.469527
Interquartile range (IQR)2.7488722

Descriptive statistics

Standard deviation1.9506997
Coefficient of variation (CV)0.55697943
Kurtosis-0.29187415
Mean3.5022832
Median Absolute Deviation (MAD)1.3291359
Skewness0.127227
Sum71299.481
Variance3.8052294
MonotonicityNot monotonic
2024-11-22T22:04:23.801359image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1476
 
7.3%
0.6931471806 822
 
4.0%
1.098612289 646
 
3.2%
1.386294361 534
 
2.6%
1.609437912 461
 
2.3%
1.791759469 423
 
2.1%
1.945910149 405
 
2.0%
2.079441542 356
 
1.7%
2.197224577 353
 
1.7%
2.302585093 322
 
1.6%
Other values (1590) 14560
71.5%
ValueCountFrequency (%)
0 1476
7.3%
0.6931471806 822
4.0%
1.098612289 646
3.2%
1.386294361 534
 
2.6%
1.609437912 461
 
2.3%
1.791759469 423
 
2.1%
1.945910149 405
 
2.0%
2.079441542 356
 
1.7%
2.197224577 353
 
1.7%
2.302585093 322
 
1.6%
ValueCountFrequency (%)
11.46952724 1
< 0.1%
11.35017121 1
< 0.1%
11.10049616 1
< 0.1%
10.97597829 1
< 0.1%
10.34563811 1
< 0.1%
10.31850687 1
< 0.1%
10.2995755 1
< 0.1%
10.28926003 1
< 0.1%
10.25456687 1
< 0.1%
10.15874973 1
< 0.1%

log_following
Real number (ℝ)

High correlation  Zeros 

Distinct620
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8593023
Minimum0
Maximum10.231928
Zeros6189
Zeros (%)30.4%
Negative0
Negative (%)0.0%
Memory size159.2 KiB
2024-11-22T22:04:23.968923image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.6094379
Q33.1354942
95-th percentile5.0049497
Maximum10.231928
Range10.231928
Interquartile range (IQR)3.1354942

Descriptive statistics

Standard deviation1.742604
Coefficient of variation (CV)0.93723543
Kurtosis-0.26062074
Mean1.8593023
Median Absolute Deviation (MAD)1.6094379
Skewness0.67987396
Sum37851.676
Variance3.0366687
MonotonicityNot monotonic
2024-11-22T22:04:24.149352image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6189
30.4%
0.6931471806 1789
 
8.8%
1.098612289 1130
 
5.6%
1.386294361 820
 
4.0%
1.609437912 621
 
3.1%
1.791759469 549
 
2.7%
1.945910149 495
 
2.4%
2.079441542 417
 
2.0%
2.197224577 380
 
1.9%
2.302585093 328
 
1.6%
Other values (610) 7640
37.5%
ValueCountFrequency (%)
0 6189
30.4%
0.6931471806 1789
 
8.8%
1.098612289 1130
 
5.6%
1.386294361 820
 
4.0%
1.609437912 621
 
3.1%
1.791759469 549
 
2.7%
1.945910149 495
 
2.4%
2.079441542 417
 
2.0%
2.197224577 380
 
1.9%
2.302585093 328
 
1.6%
ValueCountFrequency (%)
10.23192762 1
< 0.1%
9.725675811 1
< 0.1%
9.676084944 1
< 0.1%
9.386140712 1
< 0.1%
9.236884927 1
< 0.1%
9.182043773 1
< 0.1%
9.178540059 1
< 0.1%
9.162514742 1
< 0.1%
9.145054905 1
< 0.1%
8.905851181 1
< 0.1%

Interactions

2024-11-22T22:04:06.446578image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:55.029168image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:56.240100image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:57.463022image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:58.912853image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:00.097991image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:01.270367image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:02.495470image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:03.900455image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:05.161528image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:06.575489image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:55.154939image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:56.377803image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:57.604971image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:59.025031image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:00.219392image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:01.385194image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:02.627558image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:04.030744image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:05.305196image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:06.699374image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:55.265837image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:56.499051image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:57.762110image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:59.143161image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:00.335146image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:01.513315image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:02.748196image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:04.159578image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:05.421715image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:06.821728image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:55.398898image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:56.613951image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:57.894718image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:59.262172image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:00.454057image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:01.647410image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:02.868093image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:04.285259image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:05.533732image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:06.957558image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:55.522957image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:56.725994image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:58.015733image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:59.381044image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:00.570960image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:01.779160image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:03.198674image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:04.417257image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:05.659432image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:07.075472image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:55.651338image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:56.845130image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:58.289727image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:59.504017image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:00.695100image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:01.906641image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:03.313270image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:04.537920image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:05.805653image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:07.187802image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:55.759570image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:56.961479image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:58.415155image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:59.617135image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:00.815582image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:02.021426image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:03.425456image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:04.659483image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:05.938880image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:07.299526image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:55.881447image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:57.090448image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:58.539922image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:59.727477image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:00.926085image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:02.137480image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:03.535382image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:04.801415image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:06.075408image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:07.408197image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:55.994773image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:57.221197image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:58.668959image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:59.840232image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:01.039459image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:02.248211image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:03.649066image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:04.928558image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:06.195666image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:07.591717image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:56.121885image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:57.338424image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:58.790843image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:03:59.962863image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:01.155394image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:02.372070image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:03.769407image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:05.045185image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-11-22T22:04:06.325415image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Correlations

2024-11-22T22:04:24.282745image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
actor_idfollowersfollowingidlabellog_followerslog_followinglog_public_gistslog_public_repospublic_gistspublic_repossite_admintype
actor_id1.000-0.498-0.2601.0000.109-0.498-0.260-0.528-0.463-0.528-0.4630.0180.150
followers-0.4981.0000.536-0.4980.0001.0000.5360.5960.6510.5960.6510.0000.000
following-0.2600.5361.000-0.2600.0000.5361.0000.4370.5360.4370.5360.0000.000
id1.000-0.498-0.2601.0000.109-0.498-0.260-0.528-0.463-0.528-0.4630.0180.150
label0.1090.0000.0000.1091.0000.1630.1640.1400.3690.0410.0180.0060.366
log_followers-0.4981.0000.536-0.4980.1631.0000.5360.5960.6510.5960.6510.0810.224
log_following-0.2600.5361.000-0.2600.1640.5361.0000.4370.5360.4370.5360.0000.113
log_public_gists-0.5280.5960.437-0.5280.1400.5960.4371.0000.6361.0000.6360.0230.091
log_public_repos-0.4630.6510.536-0.4630.3690.6510.5360.6361.0000.6361.0000.0230.323
public_gists-0.5280.5960.437-0.5280.0410.5960.4371.0000.6361.0000.6360.0000.000
public_repos-0.4630.6510.536-0.4630.0180.6510.5360.6361.0000.6361.0000.0000.000
site_admin0.0180.0000.0000.0180.0060.0810.0000.0230.0230.0000.0001.0000.000
type0.1500.0000.0000.1500.3660.2240.1130.0910.3230.0000.0000.0001.000

Missing values

2024-11-22T22:04:08.006086image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-22T22:04:08.711137image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-11-22T22:04:09.249335image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

actor_idlabelloginidnode_idavatar_urlgravatar_idurlhtml_urlfollowers_urlfollowing_urlgists_urlstarred_urlsubscriptions_urlorganizations_urlrepos_urlevents_urlreceived_events_urltypesite_adminnamecompanybloglocationemailhireablebiotwitter_usernamepublic_repospublic_gistsfollowersfollowingcreated_atupdated_atfollowers_percentagelog_public_reposlog_public_gistslog_followerslog_following
01081405Humandlazesz1081405MDQ6VXNlcjEwODE0MDU=https://avatars.githubusercontent.com/u/1081405?v=4NaNhttps://api.github.com/users/dlazeszhttps://github.com/dlazeszhttps://api.github.com/users/dlazesz/followershttps://api.github.com/users/dlazesz/following{/other_user}https://api.github.com/users/dlazesz/gists{/gist_id}https://api.github.com/users/dlazesz/starred{/owner}{/repo}https://api.github.com/users/dlazesz/subscriptionshttps://api.github.com/users/dlazesz/orgshttps://api.github.com/users/dlazesz/reposhttps://api.github.com/users/dlazesz/events{/privacy}https://api.github.com/users/dlazesz/received_eventsUserFalseIndig BalázsNaNNaNNaNNaNNaNNaNNaN261512011-09-26 17:27:03+00:002023-10-13T11:21:10Z500.00%3.2958370.6931471.7917590.693147
113100598Humansarkiroka13100598MDQ6VXNlcjEzMTAwNTk4https://avatars.githubusercontent.com/u/13100598?v=4NaNhttps://api.github.com/users/sarkirokahttps://github.com/sarkirokahttps://api.github.com/users/sarkiroka/followershttps://api.github.com/users/sarkiroka/following{/other_user}https://api.github.com/users/sarkiroka/gists{/gist_id}https://api.github.com/users/sarkiroka/starred{/owner}{/repo}https://api.github.com/users/sarkiroka/subscriptionshttps://api.github.com/users/sarkiroka/orgshttps://api.github.com/users/sarkiroka/reposhttps://api.github.com/users/sarkiroka/events{/privacy}https://api.github.com/users/sarkiroka/received_eventsUserFalsesarkirokaNaNhttps://sarkiroka.huNaNNaNTrueI just press the buttons randomly, and the program evolves...NaN303962015-06-29 10:12:46+00:002023-10-07T06:26:14Z150.00%3.4339871.3862942.3025851.945910
222494HumanZoomQuiet22494MDQ6VXNlcjIyNDk0https://avatars.githubusercontent.com/u/22494?v=4NaNhttps://api.github.com/users/ZoomQuiethttps://github.com/ZoomQuiethttps://api.github.com/users/ZoomQuiet/followershttps://api.github.com/users/ZoomQuiet/following{/other_user}https://api.github.com/users/ZoomQuiet/gists{/gist_id}https://api.github.com/users/ZoomQuiet/starred{/owner}{/repo}https://api.github.com/users/ZoomQuiet/subscriptionshttps://api.github.com/users/ZoomQuiet/orgshttps://api.github.com/users/ZoomQuiet/reposhttps://api.github.com/users/ZoomQuiet/events{/privacy}https://api.github.com/users/ZoomQuiet/received_eventsUserFalseZoom.Quiet蟒营® py.101.camphttp://zoomquiet.ioZhuHai,China,EarthNaNTrueTime is unimportant,\r\nonly life important.zoomq1034912122212008-08-29 16:20:03+00:002023-10-02T02:11:21Z548.00%4.6443913.9120237.1008525.402677
37648032BotAlCutter7648032MDQ6VXNlcjc2NDgwMzI=https://avatars.githubusercontent.com/u/7648032?v=4NaNhttps://api.github.com/users/AlCutterhttps://github.com/AlCutterhttps://api.github.com/users/AlCutter/followershttps://api.github.com/users/AlCutter/following{/other_user}https://api.github.com/users/AlCutter/gists{/gist_id}https://api.github.com/users/AlCutter/starred{/owner}{/repo}https://api.github.com/users/AlCutter/subscriptionshttps://api.github.com/users/AlCutter/orgshttps://api.github.com/users/AlCutter/reposhttps://api.github.com/users/AlCutter/events{/privacy}https://api.github.com/users/AlCutter/received_eventsUserFalseAl CutterNaNNaNSussex, UKNaNNaNNaNNaN4908422014-05-20 18:43:09+00:002023-10-12T12:54:59Z4200.00%3.9120230.0000004.4426511.098612
42163522Humanmeetyan2163522MDQ6VXNlcjIxNjM1MjI=https://avatars.githubusercontent.com/u/2163522?v=4NaNhttps://api.github.com/users/meetyanhttps://github.com/meetyanhttps://api.github.com/users/meetyan/followershttps://api.github.com/users/meetyan/following{/other_user}https://api.github.com/users/meetyan/gists{/gist_id}https://api.github.com/users/meetyan/starred{/owner}{/repo}https://api.github.com/users/meetyan/subscriptionshttps://api.github.com/users/meetyan/orgshttps://api.github.com/users/meetyan/reposhttps://api.github.com/users/meetyan/events{/privacy}https://api.github.com/users/meetyan/received_eventsUserFalseJiajun YanNaNNaNNaNNaNTrueNaNNaN111622012-08-16 14:19:13+00:002023-10-06T11:58:41Z300.00%2.4849070.6931471.9459101.098612
527288824Humancooperspencer27288824MDQ6VXNlcjI3Mjg4ODI0https://avatars.githubusercontent.com/u/27288824?v=4NaNhttps://api.github.com/users/cooperspencerhttps://github.com/cooperspencerhttps://api.github.com/users/cooperspencer/followershttps://api.github.com/users/cooperspencer/following{/other_user}https://api.github.com/users/cooperspencer/gists{/gist_id}https://api.github.com/users/cooperspencer/starred{/owner}{/repo}https://api.github.com/users/cooperspencer/subscriptionshttps://api.github.com/users/cooperspencer/orgshttps://api.github.com/users/cooperspencer/reposhttps://api.github.com/users/cooperspencer/events{/privacy}https://api.github.com/users/cooperspencer/received_eventsUserFalseAndreas WachterAlpegahttps://www.patreon.com/buddyspencerAustriahello@buddyspencer.monsterNaNDone studying. Need challenges.BuddySp3nc3r5612272017-04-11 14:08:07+00:002023-10-11T05:59:26Z314.00%4.0430510.6931473.1354942.079442
65709Humangoofmint5709MDQ6VXNlcjU3MDk=https://avatars.githubusercontent.com/u/5709?v=4NaNhttps://api.github.com/users/goofminthttps://github.com/goofminthttps://api.github.com/users/goofmint/followershttps://api.github.com/users/goofmint/following{/other_user}https://api.github.com/users/goofmint/gists{/gist_id}https://api.github.com/users/goofmint/starred{/owner}{/repo}https://api.github.com/users/goofmint/subscriptionshttps://api.github.com/users/goofmint/orgshttps://api.github.com/users/goofmint/reposhttps://api.github.com/users/goofmint/events{/privacy}https://api.github.com/users/goofmint/received_eventsUserFalseAtsushiMOONGIFThttps://moongift.co.jpYokohama, Japanatsushi@moongift.jpTrueAdministrator of MOONGIFT that is introducing open source software everyday to Japanese engineers since 2004.NaN277113963162008-04-07 22:22:22+00:002023-09-27T09:04:56Z394.00%5.6276217.0387844.1588832.833213
71355668Humanmhutchinson1355668MDQ6VXNlcjEzNTU2Njg=https://avatars.githubusercontent.com/u/1355668?v=4NaNhttps://api.github.com/users/mhutchinsonhttps://github.com/mhutchinsonhttps://api.github.com/users/mhutchinson/followershttps://api.github.com/users/mhutchinson/following{/other_user}https://api.github.com/users/mhutchinson/gists{/gist_id}https://api.github.com/users/mhutchinson/starred{/owner}{/repo}https://api.github.com/users/mhutchinson/subscriptionshttps://api.github.com/users/mhutchinson/orgshttps://api.github.com/users/mhutchinson/reposhttps://api.github.com/users/mhutchinson/events{/privacy}https://api.github.com/users/mhutchinson/received_eventsUserFalseMartin HutchinsonGoogleNaNLondon, UKNaNNaNSenior Software Engineer at Google, working on Certificate Transparency and generalized transparency.NaN3712202012-01-19 21:57:07+00:002023-08-07T16:06:34Zinf%3.6375860.6931473.1354940.000000
859210087Humanstfuanu59210087MDQ6VXNlcjU5MjEwMDg3https://avatars.githubusercontent.com/u/59210087?v=4NaNhttps://api.github.com/users/stfuanuhttps://github.com/stfuanuhttps://api.github.com/users/stfuanu/followershttps://api.github.com/users/stfuanu/following{/other_user}https://api.github.com/users/stfuanu/gists{/gist_id}https://api.github.com/users/stfuanu/starred{/owner}{/repo}https://api.github.com/users/stfuanu/subscriptionshttps://api.github.com/users/stfuanu/orgshttps://api.github.com/users/stfuanu/reposhttps://api.github.com/users/stfuanu/events{/privacy}https://api.github.com/users/stfuanu/received_eventsUserFalseanuNaNNaNNaNNaNNaNNaNNaN272375962019-12-24 20:04:33+00:002023-10-12T11:55:01Z6.00%3.3322051.0986123.6375866.391917
95076961Humanjamieshepherd5076961MDQ6VXNlcjUwNzY5NjE=https://avatars.githubusercontent.com/u/5076961?v=4NaNhttps://api.github.com/users/jamieshepherdhttps://github.com/jamieshepherdhttps://api.github.com/users/jamieshepherd/followershttps://api.github.com/users/jamieshepherd/following{/other_user}https://api.github.com/users/jamieshepherd/gists{/gist_id}https://api.github.com/users/jamieshepherd/starred{/owner}{/repo}https://api.github.com/users/jamieshepherd/subscriptionshttps://api.github.com/users/jamieshepherd/orgshttps://api.github.com/users/jamieshepherd/reposhttps://api.github.com/users/jamieshepherd/events{/privacy}https://api.github.com/users/jamieshepherd/received_eventsUserFalseJamie Shepherd@Wikiahttp://jamie.shSan FranciscoNaNNaNHijamiesheep4291422013-07-23 23:29:34+00:002023-10-09T20:47:05Z700.00%3.7612002.3025852.7080501.098612
actor_idlabelloginidnode_idavatar_urlgravatar_idurlhtml_urlfollowers_urlfollowing_urlgists_urlstarred_urlsubscriptions_urlorganizations_urlrepos_urlevents_urlreceived_events_urltypesite_adminnamecompanybloglocationemailhireablebiotwitter_usernamepublic_repospublic_gistsfollowersfollowingcreated_atupdated_atfollowers_percentagelog_public_reposlog_public_gistslog_followerslog_following
2034818622487BotG3rrus18622487MDQ6VXNlcjE4NjIyNDg3https://avatars.githubusercontent.com/u/18622487?v=4NaNhttps://api.github.com/users/G3rrushttps://github.com/G3rrushttps://api.github.com/users/G3rrus/followershttps://api.github.com/users/G3rrus/following{/other_user}https://api.github.com/users/G3rrus/gists{/gist_id}https://api.github.com/users/G3rrus/starred{/owner}{/repo}https://api.github.com/users/G3rrus/subscriptionshttps://api.github.com/users/G3rrus/orgshttps://api.github.com/users/G3rrus/reposhttps://api.github.com/users/G3rrus/events{/privacy}https://api.github.com/users/G3rrus/received_eventsUserFalseG3rrusNaNNaNAustriaNaNNaNNaNNaN100102016-04-22 22:11:59+00:002022-07-07T19:48:21Zinf%2.3978950.0000000.6931470.000000
203491657783HumanHackerpilot1657783MDQ6VXNlcjE2NTc3ODM=https://avatars.githubusercontent.com/u/1657783?v=4NaNhttps://api.github.com/users/Hackerpilothttps://github.com/Hackerpilothttps://api.github.com/users/Hackerpilot/followershttps://api.github.com/users/Hackerpilot/following{/other_user}https://api.github.com/users/Hackerpilot/gists{/gist_id}https://api.github.com/users/Hackerpilot/starred{/owner}{/repo}https://api.github.com/users/Hackerpilot/subscriptionshttps://api.github.com/users/Hackerpilot/orgshttps://api.github.com/users/Hackerpilot/reposhttps://api.github.com/users/Hackerpilot/events{/privacy}https://api.github.com/users/Hackerpilot/received_eventsUserFalseBrian SchottNaNNaNUnited StatesNaNTrueNaNNaN37199162012-04-19 03:27:14+00:002023-10-07T18:13:52Z1517.00%3.6375862.9957324.5217891.945910
2035045903829Botalvaro-bot45903829MDQ6VXNlcjQ1OTAzODI5https://avatars.githubusercontent.com/u/45903829?v=4NaNhttps://api.github.com/users/alvaro-bothttps://github.com/alvaro-bothttps://api.github.com/users/alvaro-bot/followershttps://api.github.com/users/alvaro-bot/following{/other_user}https://api.github.com/users/alvaro-bot/gists{/gist_id}https://api.github.com/users/alvaro-bot/starred{/owner}{/repo}https://api.github.com/users/alvaro-bot/subscriptionshttps://api.github.com/users/alvaro-bot/orgshttps://api.github.com/users/alvaro-bot/reposhttps://api.github.com/users/alvaro-bot/events{/privacy}https://api.github.com/users/alvaro-bot/received_eventsUserFalseNaNNaNNaNNaNNaNNaNI am the bot account of @alvaroalemanNaN10002018-12-15 19:55:31+00:002021-07-27T14:14:25Z0.00%0.6931470.0000000.0000000.000000
203515902773Humanthomasbottonari5902773MDQ6VXNlcjU5MDI3NzM=https://avatars.githubusercontent.com/u/5902773?v=4NaNhttps://api.github.com/users/thomasbottonarihttps://github.com/thomasbottonarihttps://api.github.com/users/thomasbottonari/followershttps://api.github.com/users/thomasbottonari/following{/other_user}https://api.github.com/users/thomasbottonari/gists{/gist_id}https://api.github.com/users/thomasbottonari/starred{/owner}{/repo}https://api.github.com/users/thomasbottonari/subscriptionshttps://api.github.com/users/thomasbottonari/orgshttps://api.github.com/users/thomasbottonari/reposhttps://api.github.com/users/thomasbottonari/events{/privacy}https://api.github.com/users/thomasbottonari/received_eventsUserFalseTom BottonariNaNNaNNaNNaNNaNNaNNaN30102013-11-10 16:05:37+00:002023-08-31T14:26:08Zinf%1.3862940.0000000.6931470.000000
2035272224629Humanchrisdlogan72224629MDQ6VXNlcjcyMjI0NjI5https://avatars.githubusercontent.com/u/72224629?v=4NaNhttps://api.github.com/users/chrisdloganhttps://github.com/chrisdloganhttps://api.github.com/users/chrisdlogan/followershttps://api.github.com/users/chrisdlogan/following{/other_user}https://api.github.com/users/chrisdlogan/gists{/gist_id}https://api.github.com/users/chrisdlogan/starred{/owner}{/repo}https://api.github.com/users/chrisdlogan/subscriptionshttps://api.github.com/users/chrisdlogan/orgshttps://api.github.com/users/chrisdlogan/reposhttps://api.github.com/users/chrisdlogan/events{/privacy}https://api.github.com/users/chrisdlogan/received_eventsUserFalseChris LoganNaNNaNNaNNaNNaNNaNNaN00002020-10-01 18:30:32+00:002020-12-29T19:45:12Z0.00%0.0000000.0000000.0000000.000000
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Duplicate rows

Most frequently occurring

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953059Humanstarswan53059MDQ6VXNlcjUzMDU5https://avatars.githubusercontent.com/u/53059?v=4https://api.github.com/users/starswanhttps://github.com/starswanhttps://api.github.com/users/starswan/followershttps://api.github.com/users/starswan/following{/other_user}https://api.github.com/users/starswan/gists{/gist_id}https://api.github.com/users/starswan/starred{/owner}{/repo}https://api.github.com/users/starswan/subscriptionshttps://api.github.com/users/starswan/orgshttps://api.github.com/users/starswan/reposhttps://api.github.com/users/starswan/events{/privacy}https://api.github.com/users/starswan/received_eventsUserFalseStephen DicksStarswan Systems LtdNaNSt Albans, Englandgithub@starswan.comNaNSenior contrarian Polyglot developer. Always looking to follow tried and trusted techniques (TDD, strong process with quality focus) rather than flash tech.NaN70502009-02-09 16:29:55+00:002023-10-08T09:32:10Zinf%2.0794420.0000001.7917590.0000002